Models of neural computation: Difference between revisions

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Revision as of 16:02, 1 March 2017

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===Robustness===

A model is robust if it continues to produce the same computational results under small variations in inputs or operating parameters introduced by noise. For example, the direction of motion as computed by a robust [[motion perception|motion detector]] would not change under small changes of [[luminance]], [[contrast (vision)|contrast]] or velocity jitter.

===Gain control===