This volume surveys the entire field of optical computing. The emphasis is on breadth of coverage. The book is descriptive, the authors minimize the use of mathematics, and it is therefore most suitable for those who require an overall view of what is going on in this field. A detailed comparison is given of the capabilities of electronics and optics, and the degree to which these capabilities have been achieved is indicated. Other areas of focus include optical computing architectures, components and technologies, optical interconnects, and optical neural nets. Approximately 300 references to key works in the field are included.

Optical Computers provides the first in-depth review of the possibilities and limitations of optical data processing.

Despite the tremendous advances in performance enabled by modern architectures, there are always new applications and demands arising that require ever-increasing capabilities. Keeping up with these demands requires a deep-seated understanding of contemporary architectures in concert with a fundamental understanding of basic principles that allows one to anticipate what will be possible over the system's lifetime. Advanced Computer Architectures focuses on the design of high performance supercomputers with balanced coverage of the hardware, software structures, and application characteristics. This book is a timeless distillation of underlying principles punctuated by real-world implementations in popular current and past commercially available systems. It briefly reviews the basics of uniprocessor architecture before outlining the most popular processing paradigms, performance evaluation, and cost factor considerations. This builds to a discussion of pipeline design and vector processors, data parallel architectures, and multiprocessor systems. Rounding out the book, the final chapter explores some important current and emerging trends such as Dataflow, Grid, biology-inspired, and optical computing. More than 220 figures, tables, and equations illustrate the concepts presented. Based on the author's more than thirty years of teaching and research, Advanced Computer Architectures endows you with the tools necessary to reach the limits of existing technology, and ultimately, to break them.

Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.

Advances in Computers