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About The Book: This book fuses signal processing algorithms and VLSI circuit design to assist digital signal processing architecture developers. The author then shows how this technique can be used in applications such as: signal transmission and storage, manufacturing process quality control and assurance, autonomous mobile system control and biomedical process analysis. This new publication is a revised and expanded version.
Introductory, systematic treatment of the many interrelated aspects. Twenty-three contributions address the fundamentals, spectral estimation algorithms, image processing, land and ocean seismic data, telecommunications, 3-D object reconstructions. Alk. paper. Annotation copyright Book News, Inc. Po
So far there does not exist any theory of adaptive spatial signal processing (ASSP) for signals with uncertain parameters. This monograph is devoted to the development of this theory, which is very important in connection with wide spreading of telecommunications and radio links in the modern society. This theory can be applied for the development of effective radio communications. In the book some original approaches are proposed targeting the development of effective algorithms of ASSP with not exactly known parameters. They include both probabilistic and deterministic approaches for synthesis of robust algorithms of ASSP. The solution of problems also can be reduced to the construction of some operators for the Banach space which is presented in the book. “Methods of Signal Processing for Adaptive Antenna Arrays” targets professionals, students and PhD students in the area of telecommunications and should be useful for everybody connected with the new information technologies.
During the past two decades there has been a considerable growth in interest in problems of pattern recognition and image processing (PRIP). This inter est has created an increasing need for methods and techniques for the design of PRIP systems. PRIP involves analysis, classification and interpretation of data. Practical applications of PRIP include character recognition, re mote sensing, analysis of medical signals and images, fingerprint and face identification, target recognition and speech understanding. One difficulty in making PRIP systems practically feasible, and hence, more popularly used, is the requirement of computer time and storage. This situation is particularly serious when the patterns to be analyzed are quite complex. Thus it is of the utmost importance to investigate special comput er architectures and their implementations for PRIP. Since the advent of VLSI technology, it is possible to put thousands of components on one chip. This reduces the cost of processors and increases the processing speed. VLSI algorithms and their implementations have been recently developed for PRIP. This book is intended to document the recent major progress in VLSI system design for PRIP applications.
This book is about systolic signal processing systems: networks of signal processors with efficient data flow between the processors. It is written for students, engineers, and managers who wish a concise introduction to the key concepts and future directions of systolic processor architectures.
In this new edition of the Handbook of Signal Processing Systems, many of the chapters from the previous editions have been updated, and several new chapters have been added. The new contributions include chapters on signal processing methods for light field displays, throughput analysis of dataflow graphs, modeling for reconfigurable signal processing systems, fast Fourier transform architectures, deep neural networks, programmable architectures for histogram of oriented gradients processing, high dynamic range video coding, system-on-chip architectures for data analytics, analysis of finite word-length effects in fixed-point systems, and models of architecture. There are more than 700 tables and illustrations; in this edition over 300 are in color. This new edition of the handbook is organized in three parts. Part I motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; Part II discusses architectures for implementing these applications; and Part III focuses on compilers, as well as models of computation and their associated design tools and methodologies.
Matrix Computations on Systolic-Type Arrays provides a framework which permits a good understanding of the features and limitations of processor arrays for matrix algorithms. It describes the tradeoffs among the characteristics of these systems, such as internal storage and communication bandwidth, and the impact on overall performance and cost. A system which allows for the analysis of methods for the design/mapping of matrix algorithms is also presented. This method identifies stages in the design/mapping process and the capabilities required at each stage. Matrix Computations on Systolic-Type Arrays provides a much needed description of the area of processor arrays for matrix algorithms and of the methods used to derive those arrays. The ideas developed here reduce the space of solutions in the design/mapping process by establishing clear criteria to select among possible options as well as by a-priori rejection of alternatives which are not adequate (but which are considered in other approaches). The end result is a method which is more specific than other techniques previously available (suitable for a class of matrix algorithms) but which is more systematic, better defined and more effective in reaching the desired objectives. Matrix Computations on Systolic-Type Arrays will interest researchers and professionals who are looking for systematic mechanisms to implement matrix algorithms either as algorithm-specific structures or using specialized architectures. It provides tools that simplify the design/mapping process without introducing degradation, and that permit tradeoffs between performance/cost measures selected by the designer.