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Digital Signal Processing

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Proceedings of the 2000 Conference

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2000 conference.

Proceedings of the 1999 Conference

The annual conference on Neural Information Processing Systems (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.

Proceedings of the 1998 Conference

The annual conference on Neural Information Processing Systems (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.

Proceedings of the 1997 Conference

The annual conference on Neural Information Processing Systems (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.

Proceedings of The 1996 Conference

The annual conference on Neural Information Processing Systems (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 neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering.

Proceedings of the 1995 Conference

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.

A New Approach to Circuit Depth

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.

These twenty lectures have been developed and refined by Professor Siebert during the more than two decades he has been teaching introductory Signals and Systems courses at MIT.

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. Consideration is limited to discrete-time problems, and emphasis is placed on coarsely quantized measurements and linear, possibly time-varying systems

Edited by Mit Press

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.The literature in this area is extensive, as evidenced by the bibliography included at the end of this collection.

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