The annual conference on Neural Information Processing System (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory.
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control.
Communication Complexity describes a new intuitive model for studying circuit networks that captures the essence of circuit depth. Although the complexity of boolean functions has been studied for almost 4 decades, the main problems the inability to show a separation of any two classes, or to obtain nontrivial lower bounds remain unsolved. The communication complexity approach provides clues as to where to took for the heart of complexity and also sheds light on how to get around the difficulty of proving lower bounds.
The mathematical operation of quantization exists in many communication and control systems. The increasing demand on existing digital facilities, such as communication channels and data storage, can be alleviated by representing the same amount of information with fewer bits at the expense of more sophisticated data processing. In Estimation and Control with Quantized Measurements, Dr. Curry examines the two distinct but related problems of state variable estimation and control when the measurements are quantized.
This collection of papers is the result of a desire to make available reprints of articles on digital signal processing for use in a graduate course offered at MIT. The primary objective was to present reprints in an easily accessible form. At the same time, it appeared that this collection might be useful for a wider audience, and consequently it was decided to reproduce the articles (originally published between 1965 and 1969) in book form.
A compact view of band theory and an original treatment of transport theory in covalent semiconductors, developed from the lectures Dr. Aigrain gave as visiting Webster Professor of Electrical Engineering at MIT.