Simone G. O. Fiori

Orcid: 0000-0001-5964-7464

Affiliations:
  • Marche Polytechnic University, Ancona, Italy
  • University of Perugia, Italy (former)


According to our database1, Simone G. O. Fiori authored at least 130 papers between 1997 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Lie-group modeling and simulation of a spherical robot, actuated by a yoke-pendulum system, rolling over a flat surface without slipping.
Robotics Auton. Syst., 2024

2023
Maximum Convergence Rate Control of a Switched Electrical Network with Symmetries.
Symmetry, October, 2023

2022
Manifold Calculus in System Theory and Control - Second Order Structures and Systems.
Symmetry, 2022

Virtual Attractive-Repulsive Potentials Control Theory: A Review and an Extension to Riemannian Manifolds.
Symmetry, 2022

2021
Manifold Calculus in System Theory and Control - Fundamentals and First-Order Systems.
Symmetry, 2021

Extension of PID Regulators to Dynamical Systems on Smooth Manifolds (M-PID).
SIAM J. Control. Optim., 2021

Improvement and Assessment of a Blind Image Deblurring Algorithm Based on Independent Component Analysis.
Comput., 2021

2020
A Control-Theoretic Approach to the Synchronization of Second-Order Continuous-Time Dynamical Systems on Real Connected Riemannian Manifolds.
SIAM J. Control. Optim., 2020

Gradient-based Learning Methods Extended to Smooth Manifolds Applied to Automated Clustering.
J. Artif. Intell. Res., 2020

2019
A Closed-Form Expression of the Instantaneous Rotational Lurch Index to Evaluate Its Numerical Approximation.
Symmetry, 2019

Glomerular Filtration Rate Estimation by a Novel Numerical Binning-Less Isotonic Statistical Bivariate Numerical Modeling Method.
Inf., 2019

A comprehensive comparison of algorithms for the statistical modelling of non-monotone relationships via isotonic regression of transformed data.
Int. J. Data Anal. Tech. Strateg., 2019

Statistical Modeling of Trivariate Static Systems: Isotonic Models.
Data, 2019

2018
Smooth statistical modeling of bivariate non-monotonic data by a three-stage LUT neural system.
Neural Comput. Appl., 2018

A Mobile Acquisition System and a Method for Hips Sway Fluency Assessment.
Inf., 2018

Generalized Gaussian Kernel Adaptive Filtering.
CoRR, 2018

2017
Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces.
Neural Comput., 2017

An Improved Chaotic Optimization Algorithm Applied to a DC Electrical Motor Modeling.
Entropy, 2017

Nonlinear damped oscillators on Riemannian manifolds: Numerical simulation.
Commun. Nonlinear Sci. Numer. Simul., 2017

2016
Nonlinear damped oscillators on Riemannian manifolds: Fundamentals.
J. Syst. Sci. Complex., 2016

A Riemannian steepest descent approach over the inhomogeneous symplectic group: Application to the averaging of linear optical systems.
Appl. Math. Comput., 2016

2015
Tangent-Bundle Maps on the Grassmann Manifold: Application to Empirical Arithmetic Averaging.
IEEE Trans. Signal Process., 2015

A Smartphone-Based Acquisition System for Hips Rotation Fluency Assessment.
CoRR, 2015

Bivariate Nonisotonic Statistical Regression by a Lookup Table Neural System.
Cogn. Comput., 2015

Kolmogoroff-Nagumo mean over the affine symplectic group of matrices.
Appl. Math. Comput., 2015

2014
Auto-Regressive Moving Average Models on Complex-Valued Matrix Lie Groups.
Circuits Syst. Signal Process., 2014

A two-dimensional Poisson equation formulation of non-parametric statistical non-linear modeling.
Comput. Math. Appl., 2014

Mixed maps for learning a Kolmogoroff-Nagumo-type average element on the compact Stiefel manifold.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Empirical Arithmetic Averaging Over the Compact Stiefel Manifold.
IEEE Trans. Signal Process., 2013

Fast statistical regression in presence of a dominant independent variable.
Neural Comput. Appl., 2013

Mixed Maps for Kolmogoroff-Nagumo-Type Averaging on the Compact Stiefel Manifold
CoRR, 2013

An isotonic trivariate statistical regression method.
Adv. Data Anal. Classif., 2013

Random Clouds on Matrix Lie Groups.
Proceedings of the Geometric Science of Information - First International Conference, 2013

2012
Extended Hamiltonian Learning on Riemannian Manifolds: Numerical Aspects.
IEEE Trans. Neural Networks Learn. Syst., 2012

Learning on the compact Stiefel manifold by a cayley-transform-based pseudo-retraction map.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A method to compute averages over the compact Stiefel manifold.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

A comparison of two algorithmic recipes to parametrize rectangular orthogonal matrices.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2012

2011
Riemannian-Gradient-Based Learning on the Complex Matrix-Hypersphere.
IEEE Trans. Neural Networks, 2011

Extended Hamiltonian Learning on Riemannian Manifolds: Theoretical Aspects.
IEEE Trans. Neural Networks, 2011

Solving Minimal-Distance Problems over the Manifold of Real-Symplectic Matrices.
SIAM J. Matrix Anal. Appl., 2011

Visualization of Riemannian-manifold-valued elements by multidimensional scaling.
Neurocomputing, 2011

Statistical Nonparametric Bivariate Isotonic Regression by Look-Up-Table-Based Neural Networks.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

2010
Learning by natural gradient on noncompact matrix-type pseudo-Riemannian manifolds.
IEEE Trans. Neural Networks, 2010

A Closed-Form Solution to the Problem of Averaging over the Lie Group of Special Orthogonal Matrices.
Proceedings of the Advances in Neural Networks, 2010

A pseudo-Riemannian-gradient approach to the least-squares problem on the real symplectic group.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
An algorithm to compute averages on matrix Lie groups.
IEEE Trans. Signal Process., 2009

Computation of the Frechet mean, variance and interpolation for a pool of neural networks over the manifold of special orthogonal matrices.
Int. J. Comput. Intell. Stud., 2009

On vector averaging over the unit hypersphere.
Digit. Signal Process., 2009

Learning the Fréchet Mean over the Manifold of Symmetric Positive-Definite Matrices.
Cogn. Comput., 2009

Learning-machines-committee Averages over the Unitary Group of Matrices.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2009), 2009

Learning averages over the lie group of symmetric positive-definite matrices.
Proceedings of the International Joint Conference on Neural Networks, 2009

Learning averages over the lie group of unitary matrices.
Proceedings of the International Joint Conference on Neural Networks, 2009

2008
Geodesic-based and projection-based neural blind deconvolution algorithms.
Signal Process., 2008

Lie-group-type neural system learning by manifold retractions.
Neural Networks, 2008

A Study on Neural Learning on Manifold Foliations: The Case of the Lie Group <i>SU</i>(3).
Neural Comput., 2008

Descent methods for optimization on homogeneous manifolds.
Math. Comput. Simul., 2008

Engineering of intelligent systems (ICEIS 2006).
Neurocomputing, 2008

Leap-frog-type learning algorithms over the Lie group of unitary matrices.
Neurocomputing, 2008

Learning by Criterion Optimization on a Unitary Unimodular Matrix Group.
Int. J. Neural Syst., 2008

Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm.
Comput. Intell. Neurosci., 2008

An averaging method for a committee of special-orthogonal-group machines.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2008), 2008

Learning stepsize selection for the geodesic-based neural blind deconvolution algorithm.
Proceedings of the International Joint Conference on Neural Networks, 2008

Generation of pseudorandom numbers with arbitrary distribution by learnable look-up-table-type neural networks.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
Learning independent components on the orthogonal group of matrices by retractions.
Neural Process. Lett., 2007

Neural Systems with Numerically Matched Input-Output Statistic: Isotonic Bivariate Statistical Modeling.
Comput. Intell. Neurosci., 2007

Neural Learning by Retractions on Manifolds.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2007), 2007

Least Squares Approximate Joint Diagonalization on the Orthogonal Group.
Proceedings of the IEEE International Conference on Acoustics, 2007

Neural Learning Algorithms Based on Mappings: The Case of the Unitary Group of Matrices.
Proceedings of the Artificial Neural Networks, 2007

2006
Blind adaptation of stable discrete-time IIR filters in state-space form.
IEEE Trans. Signal Process., 2006

Neural Systems with Numerically-Matched Input-Output Statistic: Variate Generation.
Neural Process. Lett., 2006

Fixed-point neural independent component analysis algorithms on the orthogonal group.
Future Gener. Comput. Syst., 2006

Simultaneous Tracking of the Best Basis in Reduced-Rank Wiener Filter.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005
Formulation and integration of learning differential equations on the stiefel manifold.
IEEE Trans. Neural Networks, 2005

Nonlinear Complex-Valued Extensions of Hebbian Learning: An Essay.
Neural Comput., 2005

Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial.
J. Mach. Learn. Res., 2005

Geometrical methods in neural networks and learning.
Neurocomputing, 2005

2004
Fast fixed-point neural blind-deconvolution algorithm.
IEEE Trans. Neural Networks, 2004

Analysis of modified "Bussgang" algorithms (MBAs) for channel equalization.
IEEE Trans. Circuits Syst. I Regul. Pap., 2004

One-unit 'rigid-bodies' learning rule for principal/independent component analysis with application to ECT-NDE signal processing.
Neurocomputing, 2004

Relative uncertainty learning theory: an essay.
Int. J. Neural Syst., 2004

Optical Flow Estimation via Neural Singular Value Decomposition Learning.
Proceedings of the Computational Science and Its Applications, 2004

2003
Nonsymmetric PDF estimation by artificial neurons: application to statistical characterization of reinforced composites.
IEEE Trans. Neural Networks, 2003

An improved sequential method for principal component analysis.
Pattern Recognit. Lett., 2003

Neural independent component analysis by "maximum-mismatch" learning principle.
Neural Networks, 2003

Overview of independent component analysis technique with an application to synthetic aperture radar (SAR) imagery processing.
Neural Networks, 2003

Closed-Form Expressions of Some Stochastic Adapting Equations for Nonlinear Adaptive Activation Function Neurons.
Neural Comput., 2003

A feasibility study for electromagnetic pollution monitoring by electromagnetic-source localization via neural independent component analysis.
Neurocomputing, 2003

Stiefel-Manifold Learning by Improved Rigid-Body Theory Applied to ICA.
Int. J. Neural Syst., 2003

Singular Value Decomposition Learning on Double Stiefel Manifold.
Int. J. Neural Syst., 2003

2002
A theory for learning based on rigid bodies dynamics.
IEEE Trans. Neural Networks, 2002

Complex Weighted One Unit 8216 Rigid Bodies 8217 Learning Rule for Independent Component Analysis.
Neural Process. Lett., 2002

Hybrid independent component analysis by adaptive LUT activation function neurons.
Neural Networks, 2002

Notes on Bell-Sejnowski PDF-Matching Neuron.
Neural Comput., 2002

Blind deconvolution by simple adaptive activation function neuron.
Neurocomputing, 2002

A Minor Subspace Algorithm Based on Neural Stiefel Dynamics.
Int. J. Neural Syst., 2002

Unsupervised Neural Learning on Lie Group.
Int. J. Neural Syst., 2002

Notes on cost functions and estimators for 'Bussgang' adaptive blind equalization.
Eur. Trans. Telecommun., 2002

Nonsymmetric PDF approximation by artificial neurons: application to statistical characterization of reinforced composites.
Proceedings of the 2002 International Symposium on Circuits and Systems, 2002

Blind electromagnetic source separation and localization.
Proceedings of the 2002 International Symposium on Circuits and Systems, 2002

2001
On blind separation of complex-valued sources by extended Hebbian learning.
IEEE Signal Process. Lett., 2001

A contribution to (neuromorphic) blind deconvolution by flexible approximated Bayesian estimation.
Signal Process., 2001

Probability Density Estimation Using Adaptive Activation Function Neurons.
Neural Process. Lett., 2001

A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold.
Neural Comput., 2001

Image compression using principal component neural networks.
Image Vis. Comput., 2001

Probability Density Function Learning by Unsupervised Neurons.
Int. J. Neural Syst., 2001

Topics in Blind Signal Processing by Neural Networks.
Proceedings of the 12th Italian Workshop on Neural Nets, 2001

2000
An Experimental Comparison of Three PCA Neural Networks.
Neural Process. Lett., 2000

Blind signal processing by the adaptive activation function neurons.
Neural Networks, 2000

Blind separation of circularly distributed sources by neural extended APEX algorithm.
Neurocomputing, 2000

Neural MCA for robust beamforming.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000

Improved psi-APEX Algorithm for Digital Image Compression.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

A Neural Network Approach to Maximum Likelihood Estimation for Eddy-Current Back-Scattering NDE Data Inversion.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Stiefel-Grassman Flow (SGF) Learning: Further Results.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Non-Destructive Test by the Hopfield Network.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Neural blind separation of complex sources by extended APEX algorithm (EAPEX).
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

Blind deconvolution by modified Bussgang algorithm.
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

A second-order differential system for orthonormal optimization.
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

Neural blind separation of complex sources by extended Hebbian learning (EGHA).
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

An efficient architecture for independent component analysis.
Proceedings of the 1999 International Symposium on Circuits and Systems, ISCAS 1999, Orlando, Florida, USA, May 30, 1999

Non-uniform image sampling for robot motion control by the GFS neural algorithm.
Proceedings of the International Joint Conference Neural Networks, 1999

Analytical results on pseudo-polynomial functional-link neural units for blind density shaping.
Proceedings of the International Joint Conference Neural Networks, 1999

'Mechanical' neural learning and InfoMax orthonormal independent component analysis.
Proceedings of the International Joint Conference Neural Networks, 1999

Classification of eddy current NDT data by probabilistic neural networks.
Proceedings of the International Joint Conference Neural Networks, 1999

Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Weighted least-squares blind deconvolution.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

A comparison of three PCA neural techniques.
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

1998
A unified approach to laterally-connected neural NETS.
Proceedings of the 9th European Signal Processing Conference, 1998

1997
A new unsupervised neural learning rule for orthonormal signal processing.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

A new IIR-MLP learning algorithm for on-line signal processing.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

Application of the MEC Network to Principal Component Analysis and Source Separation.
Proceedings of the Artificial Neural Networks, 1997


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