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Volterra representation and Wiener-like identification of nonlinear systems: scope and limitations

Published online by Cambridge University Press:  17 March 2009

Günther Palm  and
Bertram Pöpel
Günther Palm
Affiliation:
Max-Planck-Institute for biological Cybernetics, Spemannstraβe 38, 7400 Tübingen, F.R.G.
Bertram Pöpel
Affiliation:
Department of Physiology, Freie Universität Berlin, Berlin, F.R.G.
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Extract

After the work of Marmarelis & Naka (1972, 1973) in the catfish retina, systems analysis using stochastic stimuli has had a boom in the seventies (e.g. McCann & Marmarelis, 1975; Eckert & Bishop, 1975; French & Wong, 1977; Lipson, 1975; McCann, 1974; Naka, Marmarelis & Chan, 1975; Spekreijse & Reits, 1982; Trimble & Phillips, 1978; Terzuolo et al. 1982). White-noise analysis was considered to be a general tool for investigating nonlinear systems gaining a maximum of information with a minimum of assumptions about the system. The modification of the original Wiener theory (Wiener, 1958; Cameron & Martin, 1947; McKean, 1972) by Lee & Schetzen (1965) made the theory fairly easy to implement into widely available computers and thus accessible to a larger number of experimenters.

Type
Research Article
Information
Quarterly Reviews of Biophysics , Volume 18 , Issue 2 , May 1985 , pp. 135 - 164
Copyright
Copyright © Cambridge University Press 1985

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