Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
— The semantics of neural networks can be analyzed mathematically as a distributed system of knowledge and as systems of possible worlds expressed in the knowledge. Learning in a...
Computing in nature as is the case with the human brain is an emerging research area in theoretical computer science. The present paper’s aim is to explore biological neural cell...
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...