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A Learning Algorithm for Adaptive Time-Delays in a Temporal Neural Network

dc.contributor.authorLin, Daw-Tungen_US
dc.contributor.authorDayhoff, Judith E.en_US
dc.contributor.authorLigomenides, Panos A.en_US
dc.description.abstractThe time delay neural network (TDNN) is an effective tool for speech recognition and spatiotemporal classification. This network learns by example, adapts its weights according to gradient descent, and incorporates a time delay on each interconnection. In the TDNN, time delays are fixed throughout training, and strong weights evolve for interconnections whose delay values are important to the pattern classification task. Here we present an adaptive time delay neural network (ATNN) that adapts its time delay values during training, to better accommodate to the pattern classification task. Connection strengths are adapted as well in the ATNN. We demonstrate the effectiveness of the TDNN on chaotic series prediction.en_US
dc.format.extent548420 bytes
dc.relation.ispartofseriesISR; TR 1992-59en_US
dc.subjectneural networksen_US
dc.subjectpredictive controlen_US
dc.subjectneu ral systemsen_US
dc.subjectsignal processingen_US
dc.subjectspeech processingen_US
dc.subjectIntelligent Servomechanismsen_US
dc.titleA Learning Algorithm for Adaptive Time-Delays in a Temporal Neural Networken_US
dc.typeTechnical Reporten_US

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