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Attractor density models with application to analyzing the stability of biological neural networks


An attractor modeling algorithm is introduced which draws upon techniques found in nonlineax dynamics and pattern recognition. The technique is motivated. by the need for quantitative measures that are able to assess the stability of biological neural networks which utilize nonlinear dynamics to process information.

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