State estimation and prediction based on dynamic spike train decoding: noise, adaptation, and multisensory integration
published: Aug. 5, 2008, recorded: May 2008, views: 225
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
A key requirement facing organisms, or agents in general, acting in uncertain dynamic environments is the real-time estimation and prediction of environmental states, based upon which effective actions can be selected. In this work we show how an agent may use a simple real time neural network, receiving noisy multisensory input signals, to solve these tasks effectively.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !