An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, retrieving, and deleting information. Many models address only a subset of these a...
Abstract—A new modular recurrent neural network (MRNN)based speech-recognition method that can recognize the entire vocabulary of 1280 highly confusable Mandarin syllables is pro...
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...