Literature DB >> 3801533

The identification of nonlinear biological systems: LNL cascade models.

M J Korenberg, I W Hunter.   

Abstract

Systems that can be represented by a cascade of a dynamic linear (L), a static nonlinear (N) and a dynamic linear (L) subsystem are considered. Various identification schemes that have been proposed for these LNL systems are critically reviewed with reference to the special problems that arise in the identification of nonlinear biological systems. A simulated LNL system is identified from limited duration input-output data using an iterative identification scheme.

Mesh:

Year:  1986        PMID: 3801533     DOI: 10.1007/bf00341928

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  12 in total

1.  The identification of nonlinear biological systems: Wiener and Hammerstein cascade models.

Authors:  I W Hunter; M J Korenberg
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

2.  Rectification in the goldfish retina: analysis by sinusoidal and auxiliary stimulation.

Authors:  H Spekreijse
Journal:  Vision Res       Date:  1969-12       Impact factor: 1.886

3.  Linearizing: a method for analysing and synthesizing nonlinear systems.

Authors:  H Spekreijse; H Oosting
Journal:  Kybernetik       Date:  1970-04

4.  NEXUS: a computer language for physiological systems and signal analysis.

Authors:  I W Hunter; R E Kearney
Journal:  Comput Biol Med       Date:  1984       Impact factor: 4.589

5.  Sequential analysis of the visual evoked potential system in man: nonlinear analysis of a sandwich system.

Authors:  H Spekreijse; D Reits
Journal:  Ann N Y Acad Sci       Date:  1982       Impact factor: 5.691

6.  Generation of random sequences with jointly specified probability density and autocorrelation functions.

Authors:  I W Hunter; R E Kearney
Journal:  Biol Cybern       Date:  1983       Impact factor: 2.086

7.  Two-sided linear filter identification.

Authors:  I W Hunter; R E Kearney
Journal:  Med Biol Eng Comput       Date:  1983-03       Impact factor: 2.602

8.  A comment on nonlinear analysis.

Authors:  J Victor; R Shapley
Journal:  Biophys J       Date:  1981-09       Impact factor: 4.033

9.  On the choice of noise for the analysis of the peripheral auditory system.

Authors:  C Swerup
Journal:  Biol Cybern       Date:  1978-05-05       Impact factor: 2.086

10.  A model of the peripheral auditory system.

Authors:  T F Weiss
Journal:  Kybernetik       Date:  1966-11
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  33 in total

1.  Adaptation to temporal contrast in primate and salamander retina.

Authors:  D Chander; E J Chichilnisky
Journal:  J Neurosci       Date:  2001-12-15       Impact factor: 6.167

2.  Functional asymmetries in ON and OFF ganglion cells of primate retina.

Authors:  E J Chichilnisky; Rachel S Kalmar
Journal:  J Neurosci       Date:  2002-04-01       Impact factor: 6.167

3.  A new algorithm for the identification of multiple input Wiener systems.

Authors:  D T Westwick; R E Kearney
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

4.  Structural classification of multi-input nonlinear systems.

Authors:  H W Chen; L D Jacobson; J P Gaska
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

5.  A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs.

Authors:  Oliver P Dewhirst; Natalia Angarita-Jaimes; David M Simpson; Robert Allen; Philip L Newland
Journal:  J Comput Neurosci       Date:  2012-06-23       Impact factor: 1.621

6.  Lock-and-key mechanisms of cerebellar memory recall based on rebound currents.

Authors:  Daniel Z Wetmore; Eran A Mukamel; Mark J Schnitzer
Journal:  J Neurophysiol       Date:  2007-08-01       Impact factor: 2.714

7.  Identification of complex-cell intensive nonlinearities in a cascade model of cat visual cortex.

Authors:  R C Emerson; M J Korenberg; M C Citron
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

8.  Identifying a static nonlinear structure in a biological system using noisy, sparse data.

Authors:  Joshua R Porter; John S Burg; Peter J Espenshade; Pablo A Iglesias
Journal:  J Theor Biol       Date:  2012-02-01       Impact factor: 2.691

9.  Dissection of a nonlinear cascade model for sensory encoding.

Authors:  A S French; M J Korenberg
Journal:  Ann Biomed Eng       Date:  1991       Impact factor: 3.934

10.  White noise analysis of temporal properties in simple receptive fields of cat cortex.

Authors:  M Mancini; B C Madden; R C Emerson
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

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