Covers advances in the field of computer techniques and algorithms in digital signal processing.

Get a working knowledge of digital signal processing for computer science applications The field of digital signal processing (DSP) is rapidly exploding, yet most books on the subject do not reflect the real world of algorithm development, coding for applications, and software engineering. This important new work fills the gap in the field, providing computer professionals with a comprehensive introduction to those aspects of DSP essential for working on today's cutting-edge applications in speech compression and recognition and modem design. The author walks readers through a variety of advanced topics, clearly demonstrating how even such areas as spectral analysis, adaptive and nonlinear filtering, or communications and speech signal processing can be made readily accessible through clear presentations and a practical hands-on approach. In a light, reader-friendly style, Digital Signal Processing: A Computer Science Perspective provides: * A unified treatment of the theory and practice of DSP at a level sufficient for exploring the contemporary professional literature * Thorough coverage of the fundamental algorithms and structures needed for designing and coding DSP applications in a high level language * Detailed explanations of the principles of digital signal processors that will allow readers to investigate assembly languages of specific processors * A review of special algorithms used in several important areas of DSP, including speech compression/recognition and digital communications * More than 200 illustrations as well as an appendix containing the essential mathematical background

Military service involves exposure to multiple sources of chronic, acute, and potentially traumatic stress, especially during deployment and combat. Notoriously variable, the effects of stress can be subtle to severe, immediate or delayed, impairing individual and group readiness, operational performance, and—ultimately—survival. A comprehensive compilation on the state of the science, Biobehavioral Resilience to Stress identifies key factors and characteristics that are essential to a scientifically useful and behaviorally predictive understanding of resilience to stress. Contributions from Uniquely Qualified Military and Civilian Experts Initiated by the Military Operational Medicine Research Directorate of the US Army Medical Research and Material Command (USAMRMC), this seminal volume integrates recent research and experience from military and civilian experts in behavioral and social sciences, human performance, and physiology. Each chapter is grounded in vigorous research with emphasis on relevance to a variety of real-world operations and settings, including extreme environments encountered in modern war. Logical Progression, Cross-Disciplinary Appeal Organized into four sections, the text begins with a discussion of the relevant aspects of stress in the context of military life to offer civilian readers a window into contemporary military priorities. Later chapters consider biological, physiological, and genetic factors, psychosocial aspects of resilience, and “community capacity” variables that influence psychological responses to stressful events. This multidisciplinary effort concludes with an overview of emergent themes and related issues to advance the science of resilience toward predictive research, theory, and application for all those—military and civilian—who serve in the national defense.

Digital signal processing techniques have become the method of choice in signal processing as digital computers have increased in speed, convenience, and availability. At the same time, the C language is proving itself to be a valuable programming tool for real-time computationally intensive software tasks. This book is a complete guide to digital signal processing techniques in the C language. Covers the basic principles of digital signal processing and C programming. Introduces the basic real-time DSP programming techniques and typical programming environments which are used with DSP microprocessors. Covers the basic real-time filtering techniques which are the cornerstone of one-dimensional real-time digital signal processing. For electrical engineers and computer scientists. The CD contents are on the book's main web page -- www.informit.com/title/0133373533

A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.

A best-seller in its print version, this comprehensive CD-ROM reference contains unique, fully searchable coverage of all major topics in digital signal processing (DSP), establishing an invaluable, time-saving resource for the engineering community. Its unique and broad scope includes contributions from all DSP specialties, including: telecommunications, computer engineering, acoustics, seismic data analysis, DSP software and hardware, image and video processing, remote sensing, multimedia applications, medical technology, radar and sonar applications

Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing and four-dimensional medical imaging. This self-contained guide, the only one of its kind, enables engineers to find the optimum fast algorithm for a specific application. It presents a broad range of computationally-efficient algorithms, describes their structure and implementation, and compares their relative strengths for given problems. All the necessary background mathematics is included and theorems are rigorously proved, so all the information needed to learn and apply the techniques is provided in one convenient guide. With this practical reference, researchers and practitioners in electrical engineering, applied mathematics, and computer science can reduce power dissipation for low-end applications of signal processing, and extend the reach of high-end applications.