Spectral Techniques and Fault Detection

Author: Marg Karpovsky
Publisher: Elsevier
ISBN: 032314442X
Format: PDF, ePub, Docs
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Spectral Techniques and Fault Detection focuses on the spectral techniques for the analysis, testing, and design of digital devices. This book discusses the error detection and correction in digital devices. Organized into 10 chapters, this book starts with an overview of the concepts and tools to evaluate the applicability of various spectral approaches and fault-detection techniques to the design. This text then describes the class of generalized Programmable Logic Array configurations called Encoded PLAs. Other chapters consider the two-sided Chrestenson Transform to the analysis of some pattern properties. This book describes as well a certain type of cellular arrays for highly parallel processing, namely, three-dimensional arrays. The final chapter deals with the system design methods that allow and encourage designers to incorporate the necessary distributed error correction throughout any digital system. This book is a valuable resource for graduate students and engineers working in the fields of logic design, spectral techniques, testing, and self-testing of digital devices.

Multiple Valued Logic Design

Author: G Epstein
Publisher: Routledge
ISBN: 1351429612
Format: PDF
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Multiple-Valued Logic Design: An Introduction explains the theory and applications of this increasingly important subject. Written in a clear and understandable style, the author develops the material in a skillful way. Without using a huge mathematical apparatus, he introduces the subject in a general form that includes the well-known binary logic as a special case. The book is further enhanced by more 200 explanatory diagrams and circuits, hardware and software applications with supporting PASCAL programming, and comprehensive exercises with even-numbered answers for every chapter. Requiring introductory knowledge in Boolean algebra, 2-valued logic, or 2-valued switching theory, Multiple-Valued Logic Design: An Introduction is an ideal book for courses not only in logic design, but also in switching theory, nonclassical logic, and computer arithmetic. Computer scientists, mathematicians, and electronic engineers can also use the book as a basis for research into multiple-valued logic design.

Discrete Algorithms and Complexity

Author: David S. Johnson
Publisher: Elsevier
ISBN: 1483274004
Format: PDF, Docs
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Perspectives in Computing, Volume 15: Discrete Algorithms and Complexity provides an understanding of discrete algorithms and complexity. This book covers a variety of topics, including discrete logarithm algorithms, parallel bubbling, electronic prototyping, number theoretic complexity, and linear programming. Organized into 27 chapters, this volume begins with an overview of the basic solutions of the primal and dual that can be characterized in graph-theoretic terms. This text then explores the principal partition of vertex-weighted graphs, which is utilized to solve certain assignment problems or flow problems that are formulated using such graphs. Other chapters consider a polynomial-time algorithm for finding the geodesic center of a simple polygon. This book discusses as well the three efficient algorithms for the routing problems around a rectangle. The final chapter deals with a snoopy cache multiprocessor system wherein each processor has a cache in which it stores blocks of data. This book is a valuable resource for mathematicians and researchers.

Spectral Analysis of Signals

Author: Yanwei Wang
Publisher: Morgan & Claypool Publishers
ISBN: 1598290010
Format: PDF, ePub, Mobi
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Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.

Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes

Author: Krzysztof Patan
Publisher: Springer
ISBN: 3540798722
Format: PDF, Mobi
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An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.

Computer Vision

Author: Richard Szeliski
Publisher: Springer
ISBN: 9781848829466
Format: PDF, ePub, Mobi
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Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Mathematics for Computer Science

Author: Eric Lehman
ISBN: 9789888407064
Format: PDF, ePub, Mobi
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This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.