Digital Signal Processing and Parallel Algorithms

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawb

Writing for professionals in synthetic aperture radar (SAR), the authors describe what goes on behind the high-resolution images. They examine how SAR receives signals from satellites, processes them

This book comprises selected papers of the International Conference on Signal Processing, Image Processing and Pattern Recognition, SIP 2011, held as Part of the Future Generation Information Technolo

The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are scattered in different fields. There is the need to collect all such algorithms for quick reference. Also there i

Digital Design of Signal Processing Systems discusses a spectrum of architectures and methods for effective implementation of algorithms in hardware (HW). Encompassing all facets of the subject this b

The principles of signal processing are fundamental to the operation of many everyday devices. This book introduces the basic theory of digital signal processing, with emphasis on real-world applications. Sampling, quantization, the Fourier transform, filters, Bayesian methods and numerical considerations are covered, then developed to illustrate how they are used in audio, image, and video processing and compression, and in communications. The book concludes with methods for the efficient implementation of algorithms in hardware and software. Intuitive arguments rather than mathematical ones are used wherever possible, and links between various signal processing techniques are stressed. The advantages and disadvantages of different approaches are presented in the context of real-world examples, enabling the reader to choose the best solution to a given problem. With over 200 illustrations and over 130 exercises (including solutions), this book will appeal to practitioners working in s

The principles of signal processing are fundamental to the operation of many everyday devices. This book introduces the basic theory of digital signal processing, with emphasis on real-world applications. Sampling, quantization, the Fourier transform, filters, Bayesian methods and numerical considerations are covered, then developed to illustrate how they are used in audio, image, and video processing and compression, and in communications. The book concludes with methods for the efficient implementation of algorithms in hardware and software. Intuitive arguments rather than mathematical ones are used wherever possible, and links between various signal processing techniques are stressed. The advantages and disadvantages of different approaches are presented in the context of real-world examples, enabling the reader to choose the best solution to a given problem. With over 200 illustrations and over 130 exercises (including solutions), this book will appeal to practitioners working in s

Signal processing is everywhere in modern technology. Its mathematical basis and many areas of application are the subject of this book, based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute. Emphasis is on challenges in the subject, particular techniques adapted to particular technologies, and certain advances in algorithms and theory. The book covers two main areas: computational harmonic analysis, envisioned as a technology for efficiently analysing real data using inherent symmetries; and the challenges inherent in the acquisition, processing and analysis of images and sensing data in general [EMDASH] ranging from sonar on a submarine to a neuroscientist's fMRI study.

Signal processing is everywhere in modern technology. Its mathematical basis and many areas of application are the subject of this book, based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute. Emphasis is on challenges in the subject, particular techniques adapted to particular technologies, and certain advances in algorithms and theory. The book covers two main areas: computational harmonic analysis, envisioned as a technology for efficiently analysing real data using inherent symmetries; and the challenges inherent in the acquisition, processing and analysis of images and sensing data in general [EMDASH] ranging from sonar on a submarine to a neuroscientist's fMRI study.

Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outl

Provides a thorough and accessible introduction to the fast-growing area of multirate digital signal processing covering both the fundamental theory and the practical applications. The key characteris

Developed and proven as part of a special laboratory course at the University of Texas, this unique book makes wireless communication accessible both to undergraduates and to practicing electrical eng

Help your student learn to maximize MATLAB as a computing tool to explore traditional Digital Signal Processing (DSP) topics, solve problems and gain insights. An extremely valuable supplementary text

Digital Signal Processing has undergone enormous growth in usage/implementation in the last 20 years and many engineering schools are now offering real-time DSP courses in their undergraduate curricul

Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of te

Mathematical summary for Digital Signal Processing Applications with Matlab consists of Mathematics which is not usually dealt in the DSP core subject, but used in DSP applications. Matlab programs wi

Mathematical Summary for Digital Signal Processing Applications with Matlab consists, of Mathematics which is not usually dealt in the DSP core subject, but used in DSP applications. Matlab programs w

"An excellent introductory book" (Review of the First Edition in the International Journal of Electrical Engineering Education) ".it will serve as a reference book in this area for a long time" (Revie

Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormali

Bringing together experts in multimodal signal processing, this book provides a detailed introduction to the area, with a focus on the analysis, recognition and interpretation of human communication. The technology described has powerful applications. For instance, automatic analysis of the outputs of cameras and microphones in a meeting can make sense of what is happening – who spoke, what they said, whether there was an active discussion and who was dominant in it. These analyses are layered to move from basic interpretations of the signals to richer semantic information. The book covers the necessary analyses in a tutorial manner, going from basic ideas to recent research results. It includes chapters on advanced speech processing and computer vision technologies, language understanding, interaction modeling and abstraction, as well as meeting support technology. This guide connects fundamental research with a wide range of prototype applications to support and analyze group interac

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random p

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random p

Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applicatio

"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based p

An indispensable treatment of optical signal processing--now in a convenient paperback editionThis introduction to optical signal processing offers an unparalleled look at its underlying theory and se

Despite our growing understanding of the properties and capabilities of nonlinear filters, there persists the belief among engineers that these filters are too complex to implement. This book debunks

The creation of the text really began in 1976 with the author being involved with a group of researchers at Stanford University and the Naval Ocean Systems Center, San Diego. At that time, adaptive te

For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks,

An in-depth treatment of algorithms and standards for perceptual coding of high-fidelity audio, this self-contained reference surveys and addresses all aspects of the field. Coverage includes signal p

This fully revised and updated second edition presents the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by