"Perché dovremmo studiare questo problema se non ci divertiamo a farlo ?" (Prof. Nicola Cabibbo, Theoretical Physicist)
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1997[001] S. Fiori, A. Uncini, and F. Piazza, Application of the MEC Network to Principal Component Analysis and Source Separation, in Proc. of the International Conference on Artificial Neural Networks (ICANN), pp. 571  576, 1997 (PostScript) [002] S. Fiori, P. Campolucci, A. Uncini, and F. Piazza, A New Unsupervised Neural Learning Rule for Orthonormal Signal Processing, in Proc. of the International Conference on Acoustics, Speech and Signal Processing, Vol. 4, pp. 3349  3352, 1997 (PostScript) [003] P. Campolucci, S. Fiori, A. Uncini, and F. Piazza, A New IIRMLP Learning Algorithm for OnLine Signal Processing, in Proc. of the International Conference on Acoustics, Speech and Signal Processing, Vol. 4, pp. 3293  3356, 1997 1998[004] S. Fiori, A. Uncini, and F. Piazza, GradientBased Blind Deconvolution with Flexible Approximated Bayesian Estimator, in Proc. of the International Joint Conference on Neural Networks, pp. 854  858, 1998 [005] S. Fiori, P. Bucciarelli, and F. Piazza, Blind Signal Flatting Using Warping Neural Modules, in Proceedings of the International Joint Conference on Neural Networks, Vol. 3, pp. 2312  2317, 1998 [006] S. Fiori and F. Piazza, Orthonormal StronglyConstrained Neural Learning, in Proc. of the International Joint Conference on Neural Networks, Vol. 2, pp. 1332  1337, 1998 [007] S. Fiori, A. Uncini, and F. Piazza, Neural Learning and Weight Flow on Stiefel Manifold, in Proc. of the X Italian Workshop on Neural Networks, pp. 325  333, 1998, SpringerVerlag [008] S. Fiori, A. Uncini, and F. Piazza, A New Class of APEXLike PCA Algorithms, in Proc. of the International Symposium on Circuits and Systems, Vol. III, pp. 66  69, 1998 [009] S. Fiori and F. Piazza, BLADE: A New OnLine Blind Equalization Method Based on the Burelian Distortion Measure, in Proc. of the International Symposium on Circuits and Systems, Vol. IV, pp. 441  444, 1998 [010] S. Fiori and A. Uncini, A Unified Approach to LaterallyConnected Neural Nets, in Proc. of the IX European Signal Processing Conference (EUSIPCO), Vol. I, pp. 379  382, 1998 [011] S. Fiori and F. Piazza, A Study on FunctionalLink Neural Units with Maximum Entropy Response, in Proc. of the International Conference on Artificial Neural Networks (ICANN), Vol. 2, pp. 493  498, 1998 1999[012] E. Pomponi, S. Fiori, and F. Piazza, Complex Independent Component Analysis by Nonlinear Generalized Hebbian Learning with Rayleigh Nonlinearity, in Proc. of the International Conference on Acoustics, Speech and Signal Processing, Vol. 2, pp. 1077  1080, 1999 [013] S. Fiori and F. Piazza, Weighted LeastSquares Blind Deconvolution, in Proc. of the International Conference on Acoustics, Speech and Signal Processing, Vol. 5, pp. 2507  2510, 1999 [014] S. Fiori and F. Piazza, A Comparison of Three PCA Neural Techniques, in Proc. of the European Symposium on Artificial Neural Networks (ESANN), pp. 275  280, 1999 [015] S. Fiori and F. Piazza, A SecondOrder Differential System for Orthonormal Optimization, Proc. of the International Symposium on Circuits and Systems, Vol. V, pp. 531  534, 1999 [016] S. Fiori and F. Piazza, Neural Blind Separation of Complex Sources by Extended Hebbian Learning (EGHA), in Proc. of the of International Symposium on Circuits and Systems, Vol. V, pp. 339  342, 1999 [017] S. Fiori, P. Baldassarri, and F. Piazza, An Efficient Architecture for Independent Component Analysis, in Proc. of the International Symposium on Circuits and Systems, Vol. V, pp. 335  338, 1999 [018] S. Fiori, A. Uncini, and F. Piazza, Blind Deconvolution by Modified Bussgang Algorithm, in Proc. of the International Symposium on Circuits and Systems, Vol. III, pp. 1  4, 1999 [019] S. Fiori, A. Uncini, and F. Piazza, Neural Blind Separation of Complex Sources by Extended APEX Algorithm (EAPEX), in Proc. of the International Symposium on Circuits and Systems, Vol. V, pp. 627  630, 1999 [020] S. Fiori, An Experimetal Comparison of Three PCA Neural Techniques, in Proc. of the XI Italian Workshop on Neural Networks, pp. 249  255, 1999, SpringerVerlag [021] S. Fiori and P. Burrascano, Polynomial Clusterons Exhibit Statistical Estimation Abilities, in Proc. of the XI Italian Workshop on Neural Networks, pp. 113  119, 1999, SpringerVerlag [022] S. Fiori, A. Faustini and P. Burrascano, NonUniform Image Sampling for Robot Motion Control by the GFS Algorithm, in Proc. of the International Joint Conference on Neural Networks (IJCNN'99), Vol. 3, pp. 2057  2060, July 1999 [023] S. Fiori and P. Burrascano, `Mechanical' Neural Learning and InfoMax Orthonormal Independent Component Analysis, in Proc. of the International Joint Conference on Neural Networks (IJCNN'99), Vol. 2, pp. 985  988, July 1999 [024] S. Fiori and P. Burrascano, Analytical Results on PseudoPolynomial FunctionalLink Neurons for Blind Density Shaping, in Proc. of the International Joint Conference on Neural Networks (IJCNN'99), Vol. 2, pp. 1117  1120, July 1999 [025] M. Angeli, P. Burrascano, E. Cardelli, S. Fiori, and S. Resteghini, Classification of Eddy Current NDT data by Probabilistic Neural Networks, in Proc. of the International Joint Conference on Neural Networks (IJCNN'99)  Special session paper, Vol. 6, pp. 4012 4014, July 1999 [026] A. Bianchi, P. Burrascano, E. Cardelli, and S. Fiori, Improved Classification of Eddy Current NDT Data by the RotatedKernel Probabilistic Neural Networks, in Proc. of the Electrical Non Destructive Evaluation (E'NDE), pp. 81  83, 1999 (Word97) [027] S. Fiori and P. Burrascano, Independent Component Analysis by the PFANN Neural Network, in Proc. of the International Conference on Artificial Neural Networks, Vol. II, pp. 696  701, 1999 [028] A. Bianchi, P. Burrascano, E. Cardelli, S. Fiori, and B. Tellini, Defect Identification by Eddy Current Inspection Data Classification Through Probabilistic Neural Networks with Elliptical Kernels, Proc. of COMPUMAG'99 (12th Conference on the Computation of Electromagnetic Fields), Vol. 1, pp. 180181, Sapporo (Japan), Oct. 2528, 1999 (PostScript) [029] S. Fiori, Blind Source Separation by New MWARP Algorithm, Electronics Letters, Vol. 35, No. 4, pp. 269  270, Feb. 1999 [030] S. Fiori, Entropy Optimization by the PFANN Network: Application to Independent Component Analysis, Network: Computation in Neural Systems, Vol. 10, No. 2, pp. 171  186, May 1999 (PostScript) [031] S. Fiori, Blind Deconvolution by Spectral Weighted LeastSquares Technique, Electronics Letters, Vol. 35, No. 10, pp. 776  777, May 1999 [032] P. Burrascano, S. Fiori, and M. Mongiardo, A Review of Artificial Neural Networks Applications in Microwave CAD, Int. Journal of RF and Microwave Computer Aided Engineering, Vol. 9, No. 3, pp. 158  174, 1999 (Word97) [033] S. Fiori, 'Mechanical' Neural Learning for Blind Source Separation, Electronics Letters, Vol. 35, No. 22, pp. 1963  1964, Oct. 1999 2000[034] A. Brozzetti, S. Fiori, and P. Burrascano, Inverse Neural Modeling for Non Destructive Evaluation, Proc. of Neural Computation (NC'2000), pp. 929  933, Berlin, May 2000 (PostScript) [035] A. Brozzetti, S. Fiori, P. Burrascano, and E. Cardelli, Electromagnetic Nondestructive Test (ENDT) Data Inversion by a Neural Network Approach, in Proc. of the IEEE Conference on Electromagnetic Field Computation (CFEC'2000, Milwaukee, USA), p. 362, June 2000 (PDF) [036] S. Fiori and F. Piazza, Neural MCA for Robust Beamforming, in Proc. of the International Symposium on Circuits and Systems (ISCAS'2000) vol. III, pp. 614  617, May 2000, Geneve (Switzerland) [037] S. Barcherini, L. Cipiccia, M. Maggi, S. Fiori, and P. Burrascano, NonDestructive Test by the Hopfield Network, in Proc. of the International Joint Conference on Neural Networks, (Como, Italy), Vol. VI, pp. 381  386, July 2000 (PostScript) [038] P. Burrascano, E. Cardelli, A. Faba, S. Fiori, and A. Massinelli, Numerical Analysis of EddyCurrent NonDestructive Testing (JSAEM Benchmark Problem #6  Cracks with different shapes), in Proc. of the Electromagnetic NonDestructive Evaluation (ENDEV), pp. 333  340, Budapest, June/July 2000 (PDF) [039] S. Fiori and G. Maiolini, Weighted LeastSquares Blind Deconvolution of NonMinimum Phase Systems, IEE Proceedings  Vision, Image and Signal Processing Vol. 147, No. 6, pp. 557  563, Dec. 2000 (PostScript) [040] S. Fiori, S. Costa, and P. Burrascano, Improved ψAPEX Algorithm for Digital Image Compression, in Proc. of the International Joint Conference on Neural Networks (Como, Italy), Vol. III, pp. 392  397, July 2000 [041] S. Fiori, StiefelGrassman Flow (SGF) Learning: Further Results, Proc. of International Joint Conference on Neural Networks (Como, Italy), Vol. III, pp. 343  348, July 2000 [042] S. Fiori and P. Burrascano, A Neural Network Approach to Maximum Likelihood Estimation for EddyCurrent BackScattering NDE Data Inversion, Proc. of International Joint Conference on Neural Networks (Como, Italy), Vol. V, pp. 65  70, July 2000 (PostScript) [043] S. Fiori and P. Burrascano, Neural Network Feature Selection Applied to Robot Motion Control, in Proc. of the Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Data Mining (ANNIE'2000), pp. 77  82, November 2000 [044] S. Fiori, An Experimental Comparison of Three PCA Neural Networks, Neural Processing Letters, Vol. 11, No. 3, pp. 209  218, June 2000 (PostScript) [045] S. Fiori, Blind Separation of Circularly Distributed Source Signals by the Neural Extended APEX Algorithm, Neurocomputing, Vol. 34, No. 14, pp. 239  252, August 2000 (PostScript) [046] S. Fiori and F. Piazza, A General Class of ψAPEX PCA Neural Algorithms, IEEE Transactions on Circuits and Systems  Part I, Vol 47, No. 9, pp. 1394  1397, September 2000 (PostScript) [047] S. Fiori, Blind Signal Processing by the Adaptive Activation Function Neurons, Neural Networks, Vol. 13, No. 6, pp. 597  611, August 2000 (PDF) 2001[048] P. Burrascano, E. Cardelli, A. Faba, S. Fiori and A. Massinelli, A multilayer perceptron approach to a nondestructive test problem, in Proc. of the 6th International Workshop Electromagnetic Nondestructive Evaluation (ENDE), pp. 75  81, (Budapest, Hungary, June 2830, 2000), Edited by J. Pavo, G. Vertesy, T. Takagi, S.S. Udpa for IOS PRESS (The Netherlands), 2001 (ISBN:1586031554) [049] S. Fiori and P. Bucciarelli, Probability Density Estimation Using Adaptive Activation Function Neurons, Neural Processing Letters, Vol. 13, No. 1, pp. 31  42, Feb. 2001 (PostScript) [050] S. Fiori, A Theory for Learning by Weight Flow on StiefelGrassman Manifold, Neural Computation, Vol. 13, No. 7, pp. 1625  1647, July 2001 (PostScript) [051] S. Costa and S. Fiori, Image Compression Using Principal Component Neural Networks, Image and Vision Computing Journal (special issue on "Artificial Neural Networks for Image Analysis and Computer Vision"). Vol. 19, No. 910, pp. 649  668, August 2001 (PDF) [052] S. Fiori, P. Burrascano, E. Cardelli and A. Faba, A Blind Separation Approach to Electromagnetic Source Localization and Assessment, in Proc. of the 7^{th} International Conference on Engineering Applications of Neural Networks (EANN'2001), pp. 188  191, July 1618, 2001 [053] P. Burrascano, E. Cardelli, A. Faba, S. Fiori and A. Massinelli, Application of Probabilistic Neural Networks to Eddy Current Non Destructive Test Problems, in Proc. of the 7^{th} International Conference on Engineering Applications of Neural Networks (EANN'2001), pp. 192  195, July 1618, 2001 (PDF) [054] S. Fiori, Topics in Blind Signal Processing by Neural Networks (Invited paper), in Proc. of the XII Italian Workshop on Neural Networks, (Presentation for the "2001 E.R. Caianiello International Award"), 2001. In press (SpringerVerlag) (PostScript) [055] S. Fiori, P. Burrascano and E. Cardelli, A Neural Network Approach to ECT Data Inversion for Materials Quality Evaluation, in Proc. of the IEEE Neural Networks for Signal Processing (NNSP'2001), pp. 519  528, Falmouth (MA  USA), September 2001 (PostScript) [056] S. Fiori, On Blind Separation of ComplexValued Sources by Extended Hebbian Learning, IEEE Signal Processing Letters, Vol. 8, No. 8, pp. 217  220, August 2001 (PDF) [057] S. Fiori, A Contribution to (Neuromorphic) Blind Deconvolution by Flexible Approximated Bayesian Estimation, Signal Processing, Vol. 81, No. 10, pp. 2131  2153, September 2001 (PDF) [058] S. Fiori, Probability Density Function Learning by Unsupervised Neurons, in Proc. of the International Journal of Neural Systems, Vol. 11, No. 5, 399  417, October 2001 (Compressed PostScript) [059] S. Fiori and P. Burrascano, Electromagnetic Environmental Pollution Monitoring: Source Localization by the Independent Component Analysis, in Proc. of the Third International Conference on Independent Component Analysis, and Signal Separation, pp. 575  580, San Diego, California, December 913, 2001 [060] S. Fiori and P. Burrascano, ECTData Fusion by the Independent Component Analysis for NonDestructuve Evaluation of Metallic Slabs, in Proc. of the Third International Conference on Independent Component Analysis, and Signal Separation, pp. 323  327, San Diego, California, December 913, 2001 [061] S. Fiori, Some Properties of BellSejnowski PDFMatching Neuron, in Proc. of the Third International Conference on Independent Component Analysis, and Signal Separation, pp. 194  199, San Diego, California, December 913, 2001 2002[062] S. Fiori, Notes on Cost Functions and Estimators for `Bussgang' Adaptive Blind Equalization, European Transactions on Telecommunications (ETT), Vol. 13, No. 6, pp. 631  634, November/December 2002 (PostScript) [063] P. Burrascano, S. Fiori, F.M. FrattaleMascioli, G. Martinelli, M. Panella and A. Rizzi, Visual Path Following and Obstacle Avoidance by Artificial Neural Networks. In "Enabling Technologies for the PRASSI Autonomous Robot" (S. Taraglio and V. Nanni, Ed.s), ENEA Research Institute, pp. 30  39, 2002 (Compressed PDF) [064] S. Fiori, Hybrid Independent Component Analysis by Adaptive LUT Activation Function Neurons, Neural Networks, Vol. 15, No. 1, pp. 85  94, January 2002 (PDF)> [065] S. Fiori, A Theory for Learning Based on Rigid Bodies Dynamics, IEEE Transactions on Neural Networks, Vol. 13, No. 3, pp. 521  531, May 2002 (PDF) [066] S. Fiori and P. Burrascano, Blind Electromagnetic Source Separation and Localization, International Symposium on Circuits and Systems (ISCAS'02), Vol. 1, pp. 685  688, May 2002 [067] S. Fiori and P. Burrascano, Nonsymmetric PDF approximation by artificial neurons: application to statistical characterization of reinforced composites, IEEE International Symposium on Circuits and Systems (ISCAS'02), Vol. 3, pp. 109  112, 2002 [068] S. Fiori, F. Grimani and P. Burrascano, Novel Neural Network Feature Selection Procedure by Generalization Maximization with Application to Automatic Robot Guidance, International Journal of Smart Engineering System Design, Vol. 4, No. 2, pp. 91  106, June 2002 (Compressed PostScript) [069] S. Fiori, ComplexWeighted OneUnit `RigidBodies' Learning Rule for Independent Component Analysis, Neural Processing Letters, Vol. 15, No. 3, pp. 275  282, June 2002 (PostScript) [070] L. Albini, P. Burrascano, E. Cardelli, A. Faba and S. Fiori, Neural Blind Separation for Electromagnetic Source Localization and Assessment, International Joint Conference on Neural Networks (IJCNN'02), Vol. 1, pp. 406  411, May 2002 [071] S. Fiori, Blind Deconvolution by Simple Adaptive Activation Function Neuron, Neurocomputing, Vol. 48, No. 14, pp. 763  778, October 2002 (PDF) [072] S. Fiori, A Survey of Optical Neural Networks Applications and Technology, in Proc. of the International Workshop on "Optics in Computing", (St. Petersburg  Russia), October 1417, 2002 (PDF) [073] S. Fiori, Notes on BellSejnowski PDFMatching Neuron, Neural Computation, Vol. 14, No. 12, pp. 2847  2855, December 2002 (Compressed PostScript) [074] S. Fiori, Unsupervised Neural Learning on Lie Group, International Journal of Neural Systems, Vol. 12, No.s 3 & 4, pp. 219  246, 2002 (PDF) [075] S. Fiori, InformationTheoretic Learning for FAN Network Applied to Eterokurtic Component Analysis, IEE Proceedings  Vision, Image and Signal Processing, Vol. 149, No. 6, pp. 347  354, December 2002 (PDF). An Erratum about this manuscript was published in "Erratum" by S. Fiori, IEE Proceedings  Vision, Image and Signal Processing, Vol. 150, No. 6, p. 370, December 2003 [076] S. Fiori, Blind IntrinsicallyStable 2Pole IIR Filtering, Electronics Letters, Vol. 38, no. 23, pp. 1482  1483, December 2002 [077] S. Fiori, A Minor Subspace Algorithm Based on Neural Stiefel Dynamics, International Journal of Neural Systems, Vol. 12, No. 5, pp. 339  350, 2002 (PostScript) 2003[078] J. Biagiotti, L. Torre, S. Fiori and J.M. Kenny, Statistical Design and Analysis of the Mechanical Behavior of Polypropylene Matrix Composites Reinforced With Natural Fibers, Second International Conference on EcoComposites (EcoComp 2003), Queen Mary University, London (UK), September 12, 2003 [079] S. Fiori, Overview of Independent Component Analysis Technique with an Application to Synthetic Aperture Radar (SAR) Imagery Processing, Neural Networks (Special Issue on "Neural Networks for Analysis of Complex Scientific Data: Astronomy, Geology and Geophysics"), Vol. 16, No. 34, pp. 453  467, 2003 (PDF) [080] S. Fiori, L. Albini, A. Faba, E. Cardelli and P. Burrascano Numerical Modeling for the Localization and the Assessment of Electromagnetic Field Sources, IEEE Transactions on Magnetics, Vol. 39, No. 3, pp. 1638  1641, May 2003 (PDF) [081] J. Bracco, P. Burrascano, E. Cardelli, A. Faba and S. Fiori, A possible identification and control technique of artificial EM sources, Proc. of 15th International Zurich Symposium and Technical Exhibition on Electromagnetic Compatibility (EMC 2003), pp. 291294, February 1820, 2003, Zurich (Switzerland) [082] S. Fiori, Cost Function Adaptivity in Bussgang Filtering, Electronics Letters, Vol. 39, No. 6, pp. 572  574, March 2003 (PDF) [083] S. Fiori, Extended Hebbian Learning for Blind Separation of ComplexValued Sources, IEEE Transactions on Circuits and Systems  Part II, Vol. 50, No. 4, pp. 195  202, April 2003 (PostScript) [084] Z. Wang, Y. Lee, S. Fiori, C.S. Leung and Y.S. Zhu, An Improved Sequential Method for Principal Component Analysis, Pattern Recognition Letters, Vol. 24, No. 910, pp. 1409  1415, June 2003 (Compressed PDF) [085] S. Fiori, Singular Value Decomposition Learning on Double Stiefel Manifold, International Journal of Neural Systems, Vol. 13, No. 3, pp. 155  170, June 2003 (PDF) [086] S. Fiori, NonSymmetric PDF Estimation by Artificial Neurons: Application to Statistical Characterization of Reinforced Composites, IEEE Transactions on Neural Networks, Vol. 14, No. 4, pp. 959  962, July 2003 (PDF) [087] J. Biagiotti, S. Fiori and J.M. Kenny, A New Approach For The Statistical Evaluation Of The Mechanical Properties Of Natural Fibres, IV Convegno Nazionale sulla Scienza e Tecnologia dei Materiali, Ischia Porto (NA), June 29  July 2, 2003 (Abstract) [088] S. Fiori, Neural Minor Component Analysis Approach to Robust Constrained Beamforming, IEE Proceedings  Vision, Image and Signal Processing, Vol. 150, No. 4, pp. 205  218, August 2003 (PDF) [089] S. Fiori, ClosedForm Expressions of Some Stochastic Adapting Equations for NonLinear Adaptive Activation Function Neurons, Neural Computation, Vol. 15, No. 12, pp. 2909  2929, December 2003 (PDF) [090] S. Fiori, Neural Independent Component Analysis by `MaximumMismatch' Learning Principle, Neural Networks, Vol. 16, No. 8, pp. 1201  1221, October 2003 (PDF) [091] L. Albini, P. Burrascano and S. Fiori, A Feasibility Study for Electromagnetic Pollution Monitoring by ElectromagneticSource Localization via Neural Independent Component Analysis, Neurocomputing (Special Issue on "Evolving Solutions with Neural Networks", Edited by A. Fanni and A. Uncini), Vol. 55, Issue 34, pp. 451  468, 2003 (PDF) [092] S. Fiori and R. Rossi, StiefelManifold Learning by Improved RigidBody Theory Applied to ICA, International Journal of Neural Systems, Vol. 13, No. 5, pp. 273  290, October 2003 (PDF) [093] S. Fiori, FullyMultiplicative OrthogonalGroup ICA Neural Algorithm, Electronics Letters, Vol. 39, No. 24, pp. 1737  1738, November 2003 (PDF) 2004[094] E. Celledoni and S. Fiori, Neural Learning by Geometric Integration of Reduced `RigidBody' Equations, Journal of Computational and Applied Mathematics (JCAM), Vol. 172, No. 2, pp. 247  269, December 2004 (PDF) [095] S. Fiori, On SelfConsistency of Cost Functions for Blind Signal Processing Based on Neural Bayesian Estimators, Proceedings of the 23rd Annual Conference on Bayesian Methods and Maximum Entropy in Science and Engineering, (Editors: G. Erickson and Y. Zhai), pp. 145  156, 2004 (PDF) [096] J. Biagiotti, S. Fiori, L. Torre, M.A. LópezManchado and J.M. Kenny, Mechanical Properties of Polypropylene Matrix Composites Reinforced with Natural Fibers: A Statistical Approach, Polymer Composites, Vol. 25, No. 1, pp. 26  36, 2004 (PDF) [097] S. Fiori and P. Burrascano, OneUnit `RigidBodies' Learning Rule for Principal/Independent Component Analysis with Application to ECTNDE Signal Processing, Neurocomputing, Vol. 56, No. 14, pp. 233  255, January 2004 (PDF) [098] S. Fiori, A Fast FixedPoint Neural Blind Deconvolution Algorithm, IEEE Transactions on Neural Networks, Vol. 15, No. 2, pp. 455  459, March 2004 (PDF) [099] S. Fiori, N. Del Buono and T. Politi, Optical Flow Estimation via Neural Singular Value Decomposition Learning, in Proc. of the International Conference on Computational Science and Its Applications (Session on "Matrix Approximation with Application to Science, Engineering and Computer Science"), Lecture Notes in Computer Science (3044 LNCS), Vol. II, pp. 961  970, 2004 (May 1417, S. Maria degli Angeli, Assisi (PG), Italy) (PDF) [100] S. Fiori and R. Rossi, Statistical Characterization of Some Electrical and Mechanical Phenomena by a Neural Probability Density Function Estimation Technique, Neural Network World, Vol. 4, No. 2, pp. 153  176, 2004 (PDF) [101] S. Fiori, Analysis of Modified `Bussgang' Algorithms (MBA) for Channel Equalization, IEEE Transactions on Circuits and Systems  Part I, Vol. 51, No. 8, pp. 1552  1560, August 2004 (PDF) [102] E. Frulloni and S. Fiori, EddyCurrentBased NonDestructive Evaluation Data Quality Enhancement through Independent Component Analysis, Scientific Bulletin of the Academic Computer Center in Gdansk (''TASK Quarterly'' Journal), Vol. 8, No. 3, pp. 359  375, 2004 (PDF) [103] S. Fiori, Relative Uncertainty Learning Theory: An Essay, International Journal of Neural Systems, Vol. 14, No. 5, pp. 293  311, October 2004 (PDF) 2005[104] S. Fiori, Formulation and Integration of Learning Differential Equations on the Stiefel Manifold, IEEE Transactions on Neural Networks, Vol. 16, No. 6, pp. 1697  1701, Nov. 2005 (PDF) [105] S. Fiori, NonLinear ComplexValued Extensions of Hebbian Learning: An Essay, Neural Computation, Vol. 17, No. 4, pp. 779  838, 2005 (PDF) [106] S. Fiori, QuasiGeodesic Neural Learning Algorithms over the Orthogonal Group: A Tutorial, Journal of Machine Learning Research, Vol. 6, pp. 743  781, May 2005 (PDF) [107] S. Fiori and S.i. Amari, Editorial: Special issue on ''Geometrical Methods in Neural Networks and Learning'', Neurocomputing, Vol. 67C, pp. 1  7, August 2005 (PDF)
2006[108] S. Fiori, Extrinsic Geometrical Methods For Neural Blind Deconvolution, in Proceedings of MaxEnt'06, the Twentysixth International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (CNRS, Paris, France, July 813), pp. 149  160, American Institute of Physics, Vol. 872, 2006 [109] A. Naveed, A. Hussain, I. M. Qureshi and S. Fiori, Blind Equalization of Communication Channels for Equal Energy Sources: Energy Matching Approach, Electronics Letters, Vol. 42, No. 4, pp. 247  248, February 2006 [110] S. Fiori, FixedPoint Neural Independent Component Analysis Algorithms on the Orthogonal Group, Journal of Future Generation Computer Systems (Elsevier), Vol. 22, No. 4, pp. 430  440, March 2006 [111] S. Fiori, Neural Systems with NumericallyMatched InputOutput Statistic: Variate Generation, Neural Processing Letters, Vol. 23, No. 2, pp. 143  170, April 2006 (PDF) [112] T. Tanaka and S. Fiori, Simultaneous Tracking of the Best Basis in ReducedRank Wiener Filter, International Conference on Acoustics, Speech and Signal Processing (IEEEICASSP, Toulouse, France), Vol. III, pp. 548  551, May 2006 [113] S. Fiori, Blind Adaptation of Stable DiscreteTime IIR Filters in StateSpace Form, IEEE Transactions on Signal Processing, Vol. 54, No. 7, pp. 2596  2605, July 2006 (PDF)
2007[114] S. Fiori, Neural Learning Algorithms Based on Mappings: The Case of the Unitary Group of Matrices, in Proceedings of the International Conference on Artificial Neural Networks (ICANN'07, September 913, 2007, Porto (Portugal, EU)), Lecture Notes in Computer Science (LNCS 4668), pp. 858  863, 2007 [115] T. Tanaka and S. Fiori, Least Squares Approximate Joint Diagonalization on the Orthogonal Group, Proc. of the 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, Vol. II, pp. pp. 649  652 (Honolulu, Hawaii, USA, April 1520, 2007) [116] S. Fiori, Learning Independent Components on the Orthogonal Group of Matrices by Retractions, Neural Processing Letters, Vol. 25, No. 3, pp. 187  198, June 2007 [117] S. Fiori, Neural Learning by Retractions on Manifolds, in Proc. of the 2007 IEEE International Symposium on Circuits and Systems, pp. 1293  1296 (New Orleans, USA, May 2730, 2007) [118] S. Fiori, Neural Systems with NumericallyMatched InputOutput Statistic: Isotonic Bivariate Statistical Modeling, Computational Intelligence and Neuroscience. Vol. 2007, Article ID 71859, 23 pages, 2007. DOI: 10.1155/2007/71859 2008[119] S. Fiori, LieGroupType Neural System Learning by Manifold Retractions, Neural Networks (Elsevier), Vol. 21, No. 10, pp. 1524  1529, December 2008 [120] S. Fiori, GeodesicBased and ProjectionBased Neural Blind Deconvolution Algorithms, Signal Processing, Vol. 88, No. 3, pp. 521  538, March 2008 [121] S. Fiori, A Study on Neural Learning on Manifold Foliations: The case of the Lie Group SU(3), Neural Computation, Vol. 20, No. 4, pp. 1091  1117, April 2008 [122] S. Fiori, Learning by Criterion Optimization on a Unitary Unimodular Matrix Group, International Journal of Neural Systems (Special issue on "ComplexValued Neural Networks and Neurocomputing: Novel Methods, Applications and Implementations", Guest Editors: V.S.H. Rao, G.R. Murthy, T. Nitta and I. Aizenberg), Vol. 18, No. 2, pp. 87  103, April 2008 [123] S. Fiori, Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm, Computational Intelligence and Neuroscience journal. Vol. 2008, Article ID 426080, 8 pages, 2008. DOI: 10.1155/2008/426080 [124] S. Fiori, LeapFrogType Learning Algorithms over the Lie Group of Unitary Matrices, Neurocomputing (Special issue on "Advances in Blind Signal Processing", Guest Editors: D. Erdogmus, D. Mandic and T. Tanaka), Vol. 71, No. 1012, pp. 2224  2244, June 2008 [125] S. Fiori, Estimating Independent Components by Mappings onto the Orthogonal Manifold, Scientific Bulletin of the Academic Computer Center in Gdansk (''TASK Quarterly'' Journal), Vol. 12, No. 1, pp. 105  120, 2008 [126] S. Fiori, Learning Stepsize Selection for the GeodesicBased Neural Blind Deconvolution Algorithm, Proceedings of the International Joint Conference on Neural Networks, (Hong Kong, June 16, 2008), pp. 1802  1807, 2008 [127] S. Fiori, Generation of Pseudorandom Numbers with Arbitrary Distribution by Learnable LookUpTableType Neural Networks, Proceedings of the International Joint Conference on Neural Networks, (Hong Kong, June 16, 2008), pp. 1788  1793, 2008 [128] S. Fiori and T. Tanaka, An Averaging Method for a Committee of SpecialOrthogonalGroup Machines, Proceedings of the International Symposium on Circuits and Systems, (Seattle, WA, May 1821), pp. 2170  2173, 2008 [129] A. Hussain, S. Fiori, I.M. Qureshi, T.S. Durrani, M.M. Ahmed and K. Fukushima, Engineering of Intelligent Systems (Editorial), Neurocomputing, Vol. 71, No.s 1315, pp. 2616  2618, August 2008 [130] E. Celledoni and S. Fiori, Descent Methods for Optimization on Homogeneous Manifolds, Journal of Mathematics and Computers in Simulation (Special issue on "STRUCTURAL DYNAMICAL SYSTEMS: Computational Aspects", Guest Editors: N. Del Buono, L. Lopez and T. Politi), Vol. 79, No. 4, pp. 1298  1323, December 2008 2009[131] S. Fiori and T. Tanaka, An Algorithm to Compute Averages on Matrix Lie Groups, IEEE Transactions on Signal Processing, Vol. 57, No. 12, pp. 4734  4743, December 2009 [132] S. Fiori and T. Tanaka, LearningMachinesCommittee Averages over the Unitary Group of Matrices, Proceedings of the International Symposium on Circuits and Systems (Taipei, Taiwan, May 2427, 2009), pp. 2777  2781, 2009 [133] S. Fiori and T. Tanaka, Learning Averages over the Lie Group of Symmetric PositiveDefinite Matrices, Proceedings of the International Joint Conference on Neural Networks (Atlanta, GAUSA, June 1419, 2009), pp. 828  832, 2009 [134] S. Fiori, Learning Averages over the Lie Group of Unitary Matrices, Proceedings of the International Joint Conference on Neural Networks (Atlanta, GAUSA, June 1419, 2009), pp. 833  837, 2009 [135] S. Fiori, On Vector Averaging over the Unit Hyphersphere, Digital Signal Processing (Elsevier), Vol. 19, No. 4, pp. 715  725, July 2009 [136] S. Fiori and P. Baldassarri, Approximate Joint Matrix Diagonalization by RiemannianGradientBased Optimization over the Unitary Group (With Application to Neural Multichannel Blind Deconvolution), in "Neural Computation and Particle Accelerators: Research, Technology and Applications" (ed.s: E. Chabot and H. D'Arras, Series of Neuroscience Research Progress), NOVA Publisher, 2009 [137] S. Fiori, Computation of the Fréchet Mean, Variance and Interpolation for a Pool of Neural Networks over the Manifold of Special Orthogonal Matrices, Journal of Computational Intelligence Studies, Vol. 1, No. 1, pp. 50  71, 2009 [138] S. Fiori, Learning the Fréchet Mean over the Manifold of Symmetric PositiveDefinite Matrices, Cognitive Computation (Springer). Vol. 1, No. 4, pp. 279  291, December 2009 2010[139] S. Fiori, Optimal Stepsize Schedule for a ProjectionBased Blind Deconvolution Algorithm, Proceedings of the 2nd AsiaPacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2010, 1417 December 2010, Biopolis, Singapore), pp. 393  399, 2010 [140] S. Fiori, A PseudoRiemannianGradient Approach to the LeastSquares Problem on the Real Symplectic Group, Proceedings of the 2010 International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010, Dallas (TX, USA), March 2010), pp. 1954  1957, 2010 [141] S. Fiori, Learning by Natural Gradient on Noncompact Matrixtype PseudoRiemannian Manifolds, IEEE Transactions on Neural Networks, Vol. 21, No. 5, pp. 841  852, May 2010 (PDF) [142] S. Fiori, A ClosedForm Solution to the Problem of Averaging over the Lie Group of Special Orthogonal Matrices, in L. Zhang, J. Kwok, and B.L. Lu (Eds.), Proceedings of the 2010 International Symposium on Neural Networks (ISNN 2010, Shanghai (China), June 2010), Part I, LNCS 6063, SpringerVerlag Berlin/Heidelberg, pp. 185  192, 2010 2011[143] S. Fiori, RiemannianGradientBased Learning on the Complex MatrixHypersphere, IEEE Transactions on Neural Networks, Vol. 22, No. 12, pp. 2132  2138, December 2011 (PDF) [144] S. Fiori, Averaging over the Lie Group of Optical Systems Transference Matrices, Frontiers of Electrical and Electronic Engineering in China (Springer), Special issue of the Sino foreigninterchange Workshop on Intelligence Science and Intelligent Data Engineering 2010  Part A, Vol. 6, No. 1, pp. 137  145, March 2011 (PDF) [145] S. Fiori, Visualization of RiemannianManifoldValued Elements by Multidimensional Scaling, Neurocomputing, Vol. 74, No. 6, pp. 983  992, February 2011 (PDF) [146] S. Fiori, Extended Hamiltonian Learning on Riemannian Manifolds: Theoretical Aspects, IEEE Transactions on Neural Networks, Vol. 22, No. 5, pp. 687  700, May 2011 (PDF) [147] S. Fiori, Solving MinimalDistance Problems over the Manifold of Real Symplectic Matrices, SIAM Journal on Matrix Analysis and Applications, Vol. 32, No. 3, pp. 938  968, 2011 (PDF) [148] S. Fiori, Statistical Nonparametric Bivariate Isotonic Regression by LookUpTableBased Neural Networks, Proceedings of the 2011 International Conference on Neural Information Processing (ICONIP 2011, Shanghai (China), November 1417, 2011), B.L. Lu, L. Zhang, and J. Kwok (Eds.), Part III, LNCS 7064, pp. 365  372, Springer, Heidelberg, 2011 [149] 金子哲也, 田中聡久, Simone Fiori, Stiefel多様体における平均演算, 第26回信号処理シンポジウム論文集, pp.216221, 北海道, November 2011 [T. Kaneko, T. Tanaka and S. Fiori, Averaging matrices over the Stifel manifold, in Proceeding of the 26th Signal Processing Symposium in Japan, pp. 216  221, Sapporo, Japan, November 2011 (in Japanese)] 2012[150] S. Fiori, Extended Hamiltonian Learning on Riemannian Manifolds: Numerical Aspects, IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, No. 1, pp. 7  21, January 2012 (PDF) [151] T. Kaneko, T. Tanaka and S. Fiori, A Method to Compute Averages over the Compact Stiefel Manifold, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012, Kyoto International Conference Center (Japan), March 25  30, 2012), pp. 3829  3832, 2012 [152] S. Fiori, T. Kaneko and T. Tanaka, Learning on the Compact Stiefel Manifold by a CayleyTransformBased PseudoRetraction Map, Proceedings of the International Joint Conference on Neural Networks (WCCIIJCNN 2012, Brisbane (Australia), June 10  15, 2012), pp. 3434  3441, 2012 2013[153] T. Kaneko, S. Fiori and T. Tanaka, Empirical Arithmetic Averaging over the Compact Stiefel Manifold, IEEE Transactions on Signal Processing, Vol. 61, No. 4, pp. 883  894, February 2013 (PDF) [154] S. Fiori, Neural System Learning on ComplexValued Manifolds, Chapter of the contributed book "ComplexValued Neural Networks: Advances and Applications" (A. Hirose, Editor), WileyIEEE Press  Computational Intelligence Book Series, Chapter 2, pp. 33  58, April 2013 (ISBN: 9781118344606) [155] S. Fiori, Fast Statistical Regression in Presence of a Dominant Independent Variable, Neural Computing and Applications (Springer), Special issue of the 2011 International Conference on Neural Information Processing  ICONIP'2011, Vol. 22, No. 7, pp. 1367  1378, 2013 (PDF) [156] S. Fiori, Blind Deconvolution by a Newton Method on the NonUnitary Hypersphere, International Journal of Adaptive Control and Signal Processing (Wiley), Vol. 27, No. 6, pp. 488  518, June 2013 (PDF) [157] S. Fiori, An Isotonic Trivariate Statistical Regression Method, Advances in Data Analysis and Classification (Springer), Vol. 7, No. 2, pp. 209  235, 2013 (PDF) [158] S. Fiori, Random Clouds on Matrix Lie Groups, in Proceedings of the First International Conference on Geometric Science of Information (GSI'2013, August 2830, 2013, Paris  France). Lecture Notes in Computer Science (LNCS 8085  SpringerVerlag Berlin Heidelberger), pp. 702  712, 2013 2014[159] S. Fiori, A TwoDimensional Poisson Equation Formulation of NonParametric Statistical NonLinear Modeling, Computers and Mathematics with Applications (Elsevier), Vol. 67, No. 5, pp. 1171 — 1185, March 2014 (PDF) [160] S. Fiori, AutoRegressive Moving Average Models on ComplexValued Matrix Lie Groups, Circuits, Systems & Signal Processing (Springer), Vol. 33, No. 8, pp. 2449 — 2473, 2014 [161] S. Fiori, Fast ClosedForm Trivariate Statistical Isotonic Modeling, Electronics Letters, Vol. 50, No. 9, pp. 708 — 710, April 2014 (PDF) [162] S. Fiori, T. Kaneko and T. Tanaka, Mixed Maps for Learning a KolmogoroffNagumoType Average Element on the Compact Stiefel Manifold, in Proceedings of the 2014 International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014, Florence (Italy), May 49, 2014), pp. 4518 — 4522, 2014 [163] S. Fiori, AutoRegressive MovingAverage DiscreteTime Dynamical Systems and Autocorrelation Functions on RealValued Riemannian Matrix Manifolds, Discrete and Continuous Dynamical Systems  Series B (AIMS Press), Vol. 19, No. 9, pp. 2785 — 2808, November 2014 2015[164] S. Fiori, T. Kaneko and T. Tanaka, Tangentbundle maps on the Grassmann manifold: Application to empirical arithmetic averaging, IEEE Transactions on Signal Processing, Vol. 63, N. 1, pp. 155 — 168, January 2015 (PDF) [165] S. Fiori and A. Bonci, Nonlinear secondorder dynamical systems on Riemannian manifolds, in Proceedings of the 2015 International Conference on Modeling, Simulation and Visualization Methods (WORLDCOMP'15, Las Vegas, USA, July 2730, 2015), pp. 1622, July 2015 (CSREA Press, ISBN: 1601324197) [166] S. Fiori, KolmogoroffNagumo mean over the affine symplectic group of matrices, Applied Mathematics and Computation, Vol. 266, pp. 820 — 837, September 2015 (PDF) [167] S. Fiori, T. Gong and H.K. Lee, Bivariate nonisotonic statistical regression by a lookup table neural system, Cognitive Computation, Vol. 7, No. 6, pp. 715 — 730, December 2015 (PDF) 2016[168] T. Uehara, T. Tanaka and S. Fiori, Robust averaging of covariance matrices by Riemannian geometry for motorimagery brain–computer interfacing, in Advances in Cognitive Neurodynamics (V) (Proceedings of the Fifth International Conference on Cognitive Neurodynamics, ICCN'2015, Sanya, China, June 37, 2015), pp. 347 — 353, January 2016 (ISBN: 9789811002052) [169] S. Fiori, Nonlinear damped oscillators on Riemannian manifolds: Fundamentals, Journal of Systems Science and Complexity (Springer), Vol. 29, No. 1, pp. 22 — 40, February 2016 (DOI: 10.1007/s1142401540637) (PDF, JSSC is the copyright owner) [170] S. Fiori, A Riemannian steepest descent approach over the inhomogeneous symplectic group: Application to the averaging of linear optical systems, Applied Mathematics and Computation, Vol. 283, pp. 251 — 264, June 2016 (DOI: 10.1016/j.amc.2016.02.018) (PDF) [171] S. Fiori, N. Sabino and A. Bonci, Inlab drone's attitude maneuvering fluency evaluation by a gyroscopic lurch index, in Recent Advances in Circuits, Systems, Signal Processing and Communications (Proceedings of the 10^{th} International Conference on Circuits, Systems, Signal and Telecommunications, Barcelona, Spain, February 1315, 2016), pp. 37 — 46, 2016 (ISBN: 9781618043665) 2017[172] S. Fiori, Nonlinear damped oscillators on Riemannian manifolds: Numerical simulation, Communications in Nonlinear Science and Numerical Simulation, Vol. 47, pp. 207 — 222, June 2017 (DOI: 10.1016/j.cnsns.2016.11.025) (PDF) [173] S. Fiori and S. Prifti, Exact loworder polynomial expressions to compute the KolmogoroffNagumo mean in the affine symplectic group of optical transference matrices, Linear and Multilinear Algebra, Vol. 65, No. 4, pp. 840 — 856, 2017 (DOI: 10.1080/03081087.2016.1209732) (PDF) [174] T. Uehara, M. Sartori, T. Tanaka and S. Fiori, Robust averaging of covariances for EEG recordings classification in motor imagery brain computer interfaces, Neural Computation, Vol. 29, No. 6, pp. 1631 — 1666, June 2017 (DOI: 10.1162/NECO_a_00963) [175] S. Fiori, Gyroscopic signals smoothness assessment by geometric jolt estimation, Mathematical Methods in the Applied Sciences, Vol. 40, No. 16, pp. 5893 — 5905, November 2017 (DOI: 10.1002/mma.4441) [176] S. Fiori and R. Di Filippo, An improved chaotic optimization algorithm applied to a DC electrical motor modeling, Entropy, Vol. 19, No. 12, Article No. 665, pp. 1 — 27, 2017 (DOI: 10.3390/e19120665) (Available online at the publisher as an openaccess paper. As an invited paper, the article processing charges were entirely waived.) 2018[177] J. Wang, H. Sun and S. Fiori, A Riemannian steepest descent approach for optimization on the real symplectic group, Mathematical Methods in the Applied Sciences (Wiley), Vol. 41, No. 11, pp. 4273 — 4286, July 2018 (DOI: 10.1002/mma.4890) [178] M. Sartori, S. Fiori and T. Tanaka, An experimental study to compare CSP and TSM techniques to extract features during motor imagery tasks, Chapter 3 of the contributed book ''Signal Processing and Machine Learning for BrainMachine Interfaces'' (T. Tanaka and M. Arvaneh, Ed.s), pp. 41 — 60, The Institution of Engineering and Technology (IET), 2018 (ISBN: 9781785613982) [179] S. Fiori and N. Fioranelli, Smooth statistical modeling of bivariate nonmonotonic data by a threestage LUT neural system, Neural Computing and Applications (Springer), Vol. 30, No. 4, pp. 1353 — 1368, 2018 (DOI: 10.1007/s0052101732151) (Draft for web in PDF format)[180] S. Fiori, Nondelayed synchronization of nonautonomous dynamical systems on Riemannian manifolds and its applications, Nonlinear Dynamics (Springer), Vol. 94, No. 4, pp. 3077 — 3100, December 2018 (DOI: 10.1007/s110710184546x) [181] A. Civita, S. Fiori and G. Romani, A mobile acquisition system and a method for hips sway fluency assessment, Information (MDPI, Special issue on "eHealth and Artificial Intelligence"), Vol. 9, No. 12, Article No. 321, December 2018 (DOI: 10.3390/info9120321) (Available online at the publisher as an openaccess paper. As an invited paper, the article processing charges were entirely waived.) 2019[182] S. Fiori, A comprehensive comparison of algorithms for the statistical modeling of nonmonotone relationships via isotonic regression of transformed data, International Journal of Data Analysis Techniques and Strategies (Inderscience), Vol. 11, No. 1, pp. 29 — 57, 2019 (DOI: 10.1504/IJDATS.2019.10010384) [183] S. Fiori and A. Vitali, Statistical modeling of trivariate static systems: Isotonic models, Data, Vol. 4, No. 1, Article No. 17, January 2019 (DOI: 10.3390/data4010017) (Available online at the publisher as an openaccess paper.)[184] S. N. Giles and S. Fiori, Glomerular filtration rate estimation by a novel numerical binningless isotonic statistical bivariate regression method, Information (Special issue on "eHealth and Artificial Intelligence"), Vol. 10, No. 3, Article No. 100, March 2019 (DOI: 10.3390/info10030100) (Available online at the publisher as an openaccess paper.) [185] S. Fiori, Synchronization of firstorder autonomous oscillators on Riemannian manifolds, Discrete and Continuous Dynamical Systems  Series B (AIMS), Vol. 24, No. 4, pp. 1725 — 1741, April 2019 (DOI: 10.3934/dcdsb.2018233) [186] S. Fiori, A closedform expression of the instantaneous rotational lurch index to evaluate its numerical approximation, Symmetry, Vol. 11, No. 10, Article No. 1208, September 2019 (DOI: 10.3390/sym11101208) (Available online at the publisher as an openaccess paper.) [187] S. Fiori, Model formulation over Lie groups and numerical methods to simulate the motion of gyrostats and quadrotors, Mathematics, Vol. 7, No. 10, Article No. 935, October 2019 (DOI: 10.3390/math7100935) (Available online at the publisher as an openaccess paper.) [188] J. Wang, H. Sun and S. Fiori, Empirical means on pseudoorthogonal groups, Mathematics, Vol. 7, No. 10, Article No. 940, October 2019 (DOI: 10.3390/math7100940) (Available online at the publisher as an openaccess paper.) 2020[189] S. Fiori, L. Del Rossi, M. Gigli and A. Saccuti, First order and second order learning algorithms on the special orthogonal group to compute the SVD of data matrices, Electronics, Vol. 9, No. 2, Article No. 934, February 2020 (DOI: 10.3390/electronics9020334) (Available online at the publisher as an openaccess paper.) [190] D. Polucci, M. Marchetti and S. Fiori, A novel nonisotonic statistical bivariate regression method — Application to stratigraphic data modeling and interpolation, Mathematical and Computational Applications, Vol. 25, No. 1, Article No. 15, March 2020 (DOI: 10.3390/mca25010015) (Available online at the publisher as an openaccess paper.) [191] S. Fiori, A controltheoretic approach to the synchronization of secondorder continuoustime dynamical systems on real connected Riemannian manifolds, SIAM Journal on Control and Optimization, Vol. 58, No. 2, pp. 787 — 813, 2020 (DOI: 10.1137/18M1235727) [192] T. Wada, K. Fukumori, T. Tanaka and S. Fiori, Anisotropic Gaussian kernel adaptive filtering by Liegroup dictionary learning, PLoS ONE, Vol. 15, No. 8, pp. e0237654 (DOI: 10.1371/journal.pone.0237654) [193] A. Koudounas and S. Fiori, Gradientbased learning methods extended to smooth manifolds, Journal of Artificial Intelligence Research, Vol. 68, pp. 777 — 816, 2020 (DOI: 10.1613/jair.1.12192) [194] S. Fiori, I. Cervigni, M. Ippoliti and C. Menotta, Extension of a PID control theory to Lie groups applied to synchronizing satellites and drones, IET Control Theory & Applications, Vol. 14, No. 17, pp. 2628 — 2642, 2020 (DOI: 10.1049/ietcta.2020.0226) 2021[195] S. Fiori, Extension of PID regulators to dynamical systems on smooth manifolds (MPID), SIAM Journal on Control and Optimization, 2021, Vol. 59, No. 1, pp. 78 — 102, January 2021. (DOI: 10.1137/19M1307743) [196] S. Fiori, Errorbased control systems on Riemannian state manifolds: Properties of the principal pushforward map associated to parallel transport, Mathematical Control and Related Fields, Vol. 11, No. 1, pp. 143 — 167, 2021 (DOI: 10.3934/mcrf.2020031) [197] A. Bonci, S. Fiori, H. Higashi, T. Tanaka and F. Verdini, An introductory tutorial on braincomputer interfaces and their applications, Electronics, Vol. 10, No. 5, Article No. 560, February 2021 (DOI: 10.3390/electronics10050560) (Available online at the publisher as an openaccess paper.) [198] S. Fiori, Improvement and assessment of a blind image deblurring algorithm based on independent component analysis, Computation (MDPI — This article belongs to the Section Computational Engineering), Vol. 9, No. 7, Article No. 76, July 2021 (DOI: 10.3390/computation9070076) (Available online at the publisher as an openaccess paper.) [199] A. Tarsi and S. Fiori, Liegroup modeling and numerical simulation of a helicopter, Mathematics (MDPI), Vol. 9, No. 21, Article No. 2682, October 2021 (DOI: 10.3390/math9212682) (Available online at the publisher as an openaccess paper.) [200] S. Fiori, Manifold calculus in system theory and control – Fundamentals and firstorder systems, Symmetry (MDPI), Vol. 13, No. 11, Article No. 2092, November 2021 (DOI: 10.3390/sym13112092) (Available online at the publisher as an openaccess paper.) 2022[201] L. Bigelli, F. Polenta and S. Fiori, Virtual attractiverepulsive potentials control theory: A review and an extension to Riemannian manifolds, Symmetry (MDPI), Vol. 14, No. 2, Article No. 257, January 2022 (DOI: 10.3390/sym14020257) (Available online at the publisher as an openaccess paper.) [202] S. Fiori, I. Cervigni, M. Ippoliti and C. Menotta, Synthetic nonlinear secondorder oscillators on Riemannian manifolds and their numerical simulation, Discrete and Continuous Dynamical Systems — Series B (AIMS), Vol. 27, No. 3, pp. 1227 — 1262, 2022 (DOI: 10.3934/dcdsb.2021088) [203] S. Fiori and L. Del Rossi, Minimal control effort and time Liegroup synchronization design based on proportionalderivative control, International Journal of Control, Vol. 95, No. 1, pp. 138 — 150, 2022 (DOI: 10.1080/00207179.2020.1780474) [204] S. Fiori, L. Bigelli and F. Polenta, Liegroup type quadcopter control design by dynamics replacement and the virtual attractiverepulsive potentials theory, Mathematics (MDPI), Vol. 10, No. 7, Article No. 1104, March 2022 (DOI: 10.3390/math10071104) (Available online at the publisher as an openaccess paper.) [205] A.D. Cafaro and S. Fiori, Optimization of a control law to synchronize firstorder dynamical systems on Riemannian manifolds by a transverse component, Discrete and Continuous Dynamical Systems — Series B (AIMS), Vol. 27, No. 7, pp. 3947 — 3969, July 2022 (DOI: 10.3934/dcdsb.2021213) [206] S. Fiori, Manifold calculus in system theory and control – Second order structures and systems, Symmetry (MDPI), Vol. 16, No. 4, Article No. 1144, June 2022 (DOI: 10.3390/sym14061144) (Available online at the publisher as an openaccess paper.) [207] S. Fiori, I. Cervigni, M. Ippoliti and C. Menotta, Synchronization of dynamical systems on Riemannian manifolds by an extended PIDtype control theory: Numerical evaluation, Discrete and Continuous Dynamical Systems — Series B (AIMS). Vol. 27, No. 12, pp. 7373 &mdash 7408, December 2022 (DOI: 10.3934/dcdsb.2022047) 2023[208] S. Fiori and J. Wang, External identification of a reciprocal lossy multiport circuit under measurement uncertainties by Riemannian gradient descent, Energies, Vol. 16, No. 6, Article No. 2585, March 2023 (DOI: 10.3390/en16062585) (Available online at the publisher as an openaccess paper.) [209] M. Mariani and S. Fiori, Design and simulation of a neuroevolutionary controller for a quadcopter drone, Aerospace (MDPI, Special issue on "Artificial Intelligence in Drone Applications"), Aerospace, Vol. 10, No. 5, Article No. 418, April 2023 (DOI: 10.3390/aerospace10050418) (Available online at the publisher as an openaccess paper.)
Technical Reports[A] S. Fiori, T. Kaneko and T. Tanaka, Mixed Maps for KolmogoroffNagumoType Averaging on the Compact Stiefel Manifold. Technical report available from March 7, 2013 on the arXiv public archive 

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