Recent progress in neural networks

In the past several years, much progress has been made in neural network technology. Neural networks have been used in many applications of signal processing to classify different sets of patterns. This paper presents some of the trends relevant to application of neural technology. No comprehensive review of the state of the art is attempted. Rather, the emphasis is selectively on certain current trends, as new ideas, that in the author's opinion show promise for the future. However, the reader should note that neural network technology is in a state of flux with several alternative theoretical models and approaches. The paper deals with the practical aspects of the research in neural networks. The basic concepts of neural networks and progress in learning algorithms are briefly reviewed, followed by a discussion of the trends relevant to hardware implementations of these networks. Finally, hybrids comprising neural networks, expert systems, and genetic algorithms are considered.