Neural Information Processing and VLSI - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Information Processing and VLSI write by Bing J. Sheu. This book was released on 2012-12-06. Neural Information Processing and VLSI available in PDF, EPUB and Kindle. Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.
Analog VLSI
Analog VLSI - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analog VLSI write by Mohammed Ismail. This book was released on 1994. Analog VLSI available in PDF, EPUB and Kindle. This book presents the first comprehensive treatment of analog VLSI design for signal and information processing applications by blending the basic design concepts of both traditional and contemporary analog VLSI. The breadth and level of details of topics covered are unique, reflecting the birth of a new generation of analog VLSI circuits. Each chapter provides basic introductory material in a tutorial manner, with examples or case studies at the circuit and/or system level. Outstanding features of the text include coverage of the latest in analog VLSI putting students and practicing engineers on the cutting edge of this exciting field; thorough coverage of topics unique to this book including low-voltage, BiCMOS, current-mode and neural information processing, oversampled data converters, statistical design, analog testability, analog CAD, analog layout, and analog VLSI interconnects; avoids lengthy coverage of device physics and IC fabrication and goes straight to the design and applications of analog VLSI circuits; extensive use of SPICE in numerous examples and problem sets; worked examples (from a realistic-silicon chip) and end-of-chapter problems assist reader comprehension; and an instructor's manual containing a complete listing of problem solutions and SPICE netlists.
Advances in Neural Information Processing Systems 17
Advances in Neural Information Processing Systems 17 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances in Neural Information Processing Systems 17 write by Lawrence K. Saul. This book was released on 2005. Advances in Neural Information Processing Systems 17 available in PDF, EPUB and Kindle. Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.
VLSI for Artificial Intelligence and Neural Networks
VLSI for Artificial Intelligence and Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook VLSI for Artificial Intelligence and Neural Networks write by Jose G. Delgado-Frias. This book was released on 2012-12-06. VLSI for Artificial Intelligence and Neural Networks available in PDF, EPUB and Kindle. This book is an edited selection of the papers presented at the International Workshop on VLSI for Artifidal Intelligence and Neural Networks which was held at the University of Oxford in September 1990. Our thanks go to all the contributors and especially to the programme committee for all their hard work. Thanks are also due to the ACM-SIGARCH, the IEEE Computer Society, and the lEE for publicizing the event and to the University of Oxford and SUNY-Binghamton for their active support. We are particularly grateful to Anna Morris, Maureen Doherty and Laura Duffy for coping with the administrative problems. Jose Delgado-Frias Will Moore April 1991 vii PROLOGUE Artificial intelligence and neural network algorithms/computing have increased in complexity as well as in the number of applications. This in tum has posed a tremendous need for a larger computational power than can be provided by conventional scalar processors which are oriented towards numeric and data manipulations. Due to the artificial intelligence requirements (symbolic manipulation, knowledge representation, non-deterministic computations and dynamic resource allocation) and neural network computing approach (non-programming and learning), a different set of constraints and demands are imposed on the computer architectures for these applications.
Learning on Silicon
Learning on Silicon - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Learning on Silicon write by G. Cauwenberghs. This book was released on 1999-06-30. Learning on Silicon available in PDF, EPUB and Kindle. Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
