Analog Vlsi

An introduction to the design of analog VLSI circuits. Neuromorphic engineers work to improve the performance of artificial systems through the development of chips and systems that process information collectively using primarily analog circuits. This book presents the central concepts required for the creative and successful design of analog VLSI circuits. The discussion is weighted toward novel circuits that emulate natural signal processing. Unlike most circuits in commercial or industrial applications, these circuits operate mainly in the subthreshold or weak inversion region. Moreover, their functionality is not limited to linear operations, but also encompasses many interesting nonlinear operations similar to those occurring in natural systems. Topics include device physics, linear and nonlinear circuit forms, translinear circuits, photodetectors, floating-gate devices, noise analysis, and process technology.

A self-contained text, suitable for a broad audience. Presents basic concepts in electronics, transistor physics, and neurobiology for readers without backgrounds in those areas. Annotation copyrighted by Book News, Inc., Portland, OR

An Analog VLSI System for Stereoscopic Vision investigates the interaction of the physical medium and the computation in both biological and analog VLSI systems by synthesizing a functional neuromorphic system in silicon. In both the synthesis and analysis of the system, a point of view from within the system is adopted rather than that of an omniscient designer drawing a blueprint. This perspective projects the design and the designer into a living landscape. The motivation for a machine-centered perspective is explained in the first chapter. The second chapter describes the evolution of the silicon retina. The retina accurately encodes visual information over orders of magnitude of ambient illumination, using mismatched components that are calibrated as part of the encoding process. The visual abstraction created by the retina is suitable for transmission through a limited bandwidth channel. The third chapter introduces a general method for interchip communication, the address-event representation, which is used for transmission of retinal data. The address-event representation takes advantage of the speed of CMOS relative to biological neurons to preserve the information of biological action potentials using digital circuitry in place of axons. The fourth chapter describes a collective circuit that computes stereodisparity. In this circuit, the processing that corrects for imperfections in the hardware compensates for inherent ambiguity in the environment. The fifth chapter demonstrates a primitive working stereovision system. An Analog VLSI System for Stereoscopic Vision contributes to both computer engineering and neuroscience at a concrete level. Through the construction of a working analog of biological vision subsystems, new circuits for building brain-style analog computers have been developed. Specific neuropysiological and psychophysical results in terms of underlying electronic mechanisms are explained. These examples demonstrate the utility of using biological principles for building brain-style computers and the significance of building brain-style computers for understanding the nervous system.

The explosive growth and development of the integrated circuit market over the last few years have been mostly limited to the digital VLSI domain. The difficulty of automating the design process in the analog domain, the fact that a general analog design methodology remained undefined, and the poor performance of earlier tools have left the analog

Neurobiology research suggests that information can be represented by the location of an activity spot in a population of cells (`place coding'), and that this information can be processed by means of networks of interconnections. Place Coding in Analog VLSI defines a representation convention of similar flavor intended for analog-integrated circuit design. It investigates its properties and suggests ways to build circuits on the basis of this coding scheme. In this electronic version of place coding, numbers are represented by the state of an array of nodes called a map, and computation is carried out by a network of links. In the simplest case, a link is just a wire connecting a node of an input map to a node of an output map. In other cases, a link is an elementary circuit cell. Networks of links are somewhat reminiscent of look-up tables in that they hardwire an arbitrary function of one or several variables. Interestingly, these structures are also related to fuzzy rules, as well as some types of artificial neural networks. The place coding approach provides several substantial benefits over conventional analog design: Networks of links can be synthesized by a simple procedure whatever the function to be computed. Place coding is tolerant to perturbations and noise in current-mode implementations. Tolerance to noise implies that the fundamental power dissipation limits of conventional analog circuits can be overcome by using place coding. The place coding approach is illustrated by three integrated circuits computing non-linear functions of several variables. The simplest one is made up of 80 links and achieves submicrowatt power consumption in continuous operation. The most complex one incorporates about 1800 links for a power consumption of 6 milliwatts, and controls the operation of an active vision system with a moving field of view. Place Coding in Analog VLSI is primarily intended for researchers and practicing engineers involved in analog and digital hardware design (especially bio-inspired circuits). The book is also a valuable reference for researchers and students in neurobiology, neuroscience, robotics, fuzzy logic and fuzzy control.

This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks. The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts.

Cellular Neural Networks and Analog VLSI brings together in one place important contributions and up-to-date research results in this fast moving area. Cellular Neural Networks and Analog VLSI serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

Adaptive Analog VLSI Neural Systems is the first practical book on neural networks learning chips and systems. It covers the entire process of implementing neural networks in VLSI chips, beginning with the crucial issues of learning algorithms in an analog framework and limited precision effects, and giving actual case studies of working systems. The approach is systems and applications oriented throughout, demonstrating the attractiveness of such an approach for applications such as adaptive pattern recognition and optical character recognition. Dr Jabri and his co-authors from AT&T Bell Laboratories, Bellcore and the University of Sydney provide a comprehensive introduction to VLSI neural networks suitable for research and development staff and advanced students.