Structural classification of multi-input nonlinear systems

DOI10.1007/BF00202751zbMath0708.93038WikidataQ52506822 ScholiaQ52506822MaRDI QIDQ920897

Elsie Sterbin Gottlieb

Publication date: 1990

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

zbMATH Keywords

parameter estimationVolterra kernelnew structural classificationtwo-input nonlinear structureWiener kernel

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Multivariable systems, multidimensional control systems (93C35) General systems theory (93A99)

Related Items

A new algorithm for the identification of multiple input Wiener systems

Cites Work

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• The identification of nonlinear biological systems: LNL cascade models
• The identification of nonlinear biological systems: Wiener and Hammerstein Cascade models
• Identification of MGB cells by Volterra kernels. II. Towards a functional classification of cells
• Identification of MGB cells by Volterra kernels. III. A glance into the black box
• Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics
• Identification of systems containing linear dynamic and static nonlinear elements
• Practical nonlinear system analysis by Wiener kernel estimation in the frequency domain
• Identification of MGB cells by Volterra kernels. I. Prediction of responses to species specific vocalizations
• Uniqueness of a basic nonlinear structure
• Measuring Volterra kernels
• Structural classification of non-linear systems by input and output measurements
• Differential models and modelling
• The mathematical foundations of associated expansions for mildly nonlinear systems
• Nonlinear systems analysis with non-Gaussian white stimuli; General basis functionals and kernels (Corresp.)
• Identification of non-linear systems using correlation analysis and pseudorandom inputs
• Wiener-like fourier kernels for nonlinear system identification and synthesis (nonanalytic cascade, bilinear, and feedback cases)
• Expansions for Nonlinear Systems*
• Measurement of the Kernels of a Non-linear System of Finite Order†
• A New Method for Minimising a Sum of Squares without Calculating Gradients