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Unformatted text preview: Outline of the Lecture Outline of the Lecture Energy Minimization Energy Minimization Energy Motion Aperture Problem Energy Motion Aperture Problem Regularization Regularization One Can Understand Some One Can Understand Some Network Computations as Network Computations as Energy Minimization Energy Minimization Swimming uses half centers, with cross inhibition ending mainly by local inhibition. The bifurcation diagram shows fixed points and limit cycles of varying frequencies as one modulates the tonic excitation to C neurons). David Marr’s three levels of understanding computations. To understand the computation of a neural network, consider a simple feedforward case. A network like this is a resistive network, which, in steady state, minimizes electrical energy. Computations performed by neural networks can be expressed as energy minimization. The advantage to do so is emphasizing the computational strategy not the implementation. Example:...
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This note was uploaded on 06/08/2009 for the course BME 575L taught by Professor Grzywacz during the Spring '09 term at USC.
 Spring '09
 Grzywacz

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