Calculation of the Volterra kernels of nonlinear dynamic systems using an artificial neural network

DOI10.1007/BF00202758zbMath0805.92002MaRDI QIDQ1337251

Jonathan Wray, Gary G. R. Green

Publication date: 2 February 1995

Published in: Biological Cybernetics (Search for Journal in Brave)

zbMATH Keywords

artificial neural networksVolterra seriesVolterra kernelToeplitz matrix inversion technique

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Series expansions (e.g., Taylor, Lidstone series, but not Fourier series) (41A58)

Related Items (7)

Third-order reverse correlation analysis of muscle spindle primary afferent fiber responses to random muscle stretch ⋮ Phase-amplitude coordinate-based neural networks for inferring oscillatory dynamics ⋮ Multiwavelet constructions and Volterra kernel identification ⋮ Volterra Kernel Identification Using Triangular Wavelets ⋮ A simple method to synchronize chaotic systems and its application to secure communications ⋮ Multi-variable Volterra kernels identification using time-delay neural networks: application to unsteady aerodynamic loading ⋮ A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression

Uses Software

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Cites Work

• The spectro-temporal receptive field. A functional characteristic of auditory neurons
• Multilayer feedforward networks are universal approximators
• An algebraic approach to nonlinear functional expansions
• The Volterra Representation and the Wiener Expansion: Validity and Pitfalls
• Measurement of the Kernels of a Non-linear System of Finite Order†
• Approximation by superpositions of a sigmoidal function
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