Literature DB >> 2911347

The recent excitement about neural networks.

F Crick1.   

Abstract

The remarkable properties of some recent computer algorithms for neural networks seemed to promise a fresh approach to understanding the computational properties of the brain. Unfortunately most of these neural nets are unrealistic in important respects.

Mesh：

Year:  1989        PMID： 2911347     DOI： 10.1038/337129a0

Source DB:  PubMed          Journal:  Nature        ISSN： 0028-0836            Impact factor:   49.962


  53 in total

1.  Computational analyses in cognitive neuroscience: in defense of biological implausibility.

Authors:  I E Dror; D P Gallogly
Journal:  Psychon Bull Rev       Date:  1999-06

2.  Oscillations and chaos in neural networks: an exactly solvable model.

Authors:  L P Wang; E E Pichler; J Ross
Journal:  Proc Natl Acad Sci U S A       Date:  1990-12       Impact factor: 11.205

3.  Variable threshold as a model for selective attention, (de)sensitization, and anesthesia in associative neural networks.

Authors:  L Wang; J Ross
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

4.  Combining neural network and genetic algorithm for prediction of lung sounds.

Authors:  Inan Güler; Hüseyin Polat; Uçman Ergün
Journal:  J Med Syst       Date:  2005-06       Impact factor: 4.460

5.  Neural networks for perceptual processing: from simulation tools to theories.

Authors:  Kevin Gurney
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2007-03-29       Impact factor: 6.237

6.  Possible dual effect of synapses that are putatively purely excitatory or purely inhibitory: bases in stability theory and implications for neural network behavior.

Authors:  R Davenport; E Jakobsson; B Gerber
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

7.  Saccade control in a simulated robot camera-head system: neural net architectures for efficient learning of inverse kinematics.

Authors:  P Dean; J E Mayhew; N Thacker; P M Langdon
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

8.  A more biologically plausible learning rule for neural networks.

Authors:  P Mazzoni; R A Andersen; M I Jordan
Journal:  Proc Natl Acad Sci U S A       Date:  1991-05-15       Impact factor: 11.205

9.  Interactions of neural networks: models for distraction and concentration.

Authors:  L P Wang; J Ross
Journal:  Proc Natl Acad Sci U S A       Date:  1990-09       Impact factor: 11.205

10.  Synchronous neural networks of nonlinear threshold elements with hysteresis.

Authors:  L Wang; J Ross
Journal:  Proc Natl Acad Sci U S A       Date:  1990-02       Impact factor: 11.205
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