Advances In Nonlinear Signal And Image Processing Eurasip Book Series On Signal Processing And Communications

The interest in nonlinear methods in signal processing is steadily increasing, since nowadays the advances in computational capacities make it possible to implement sophisticated nonlinear processing techniques which in turn allow remarkable improvements with respect to standard and well-consolidated linear processing approaches. The aim of the book is to present a review of emerging new areas of interest involving nonlinear signal and image processing theories, techniques, and tools. More than 30 leading researchers have contributed to this book covering the major topics relevant to nonlinear signal processing. These topics include recent theoretical contributions in different areas of digital filtering and a number of applications in genomics, speech analysis and synthesis, communication system, active noise control, digital watermarking, feature extraction, texture analysis, and color image processing. The book is intended as a reference for recent advances and new applications of theories, techniques, and tools in the area of nonlinear signal processing. The target audience are graduate students and practitioners working on modern signal processing applications.

The interest in nonlinear methods in signal processing is steadily increasing, since nowadays the advances in computational capacities make it possible to implement sophisticated nonlinear processing techniques which in turn allow remarkable improvements with respect to standard and well-consolidated linear processing approaches. The aim of the book is to present a review of emerging new areas of interest involving nonlinear signal and image processing theories, techniques, and tools. More than 30 leading researchers have contributed to this book covering the major topics relevant to nonlinear signal processing. These topics include recent theoretical contributions in different areas of digital filtering and a number of applications in genomics, speech analysis and synthesis, communication system, active noise control, digital watermarking, feature extraction, texture analysis, and color image processing. The book is intended as a reference for recent advances and new applications of theories, techniques, and tools in the area of nonlinear signal processing. The target audience are graduate students and practitioners working on modern signal processing applications.

Nonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical. This book details recent advances in nonl

This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its application Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved Quick tutorial reviews of important and emerging topics of research in machine learning Presents core principles in signal processing theory and shows their applications Reference content on core principles, technologies, algorithms and applications Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity.

The principles of signal processing are using widely in telecommunications, control systems, sensors, smartphones, tablets, TV, video- and photo-cameras, computers, audio systems, etc. Written by 43 experienced and well-respected experts from universities, research centres and industry from 14 countries: Argentina, Australia, Brazil, China, Ecuador, France, Japan, Poland, Portugal, Spain, Switzerland, UK, Ukraine and USA the 'Advances is Signal Processing: Reviews', Vol. 1, Book Series, contains 13 chapters from the signals and systems theory to real-world applications. The authors discuss existing issues and ways to overcome these problems as well as the new challenges arising in the field. The book concludes with methods for the efficient implementation of algorithms in hardware and software. The advantages and disadvantages of different approaches are presented in the context of practical examples.

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. The book is directed to the Ph.D. students, professors, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems. The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes.