Digital signal processing (DSP)

Unlike many books on Asynchronous Transfer Mode, this text approaches the subject systematically and reflects the state-of-the-art technology being applied throughout the world today.

The European Computing Conference offers a unique forum for establishing new collaborations within present or upcoming research projects, exchanging useful ideas, presenting recent research results, participating in discussions and establishing new academic collaborations, linking university with the industry.

This textbook presents the fundamentals of audio coding, used to compress audio and music signals, using Python programs both as examples to illustrate the principles and for experiments for the reader.

This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challenges posed by a variety of safety and surveillance applications.

The purpose of this book is to give the reader two things, to paraphrase Mark Twain: Roots to know the basics of modeling networks and Wings to fly away and attempt modeling other proposed systems of interest.

With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

This book presents a novel logarithmic conversion architecture based on cross-coupled inverter.

The book covers a wide range of wireless communication and network technologies, and will help readers understand the role of wireless technologies in applications touching on various spheres of human life, e.

Modeling and Simulation Tools for Emerging Telecommunication Networks contains over 20 articles by well-known scientists and engineers reflecting the advances in modeling and simulation for telecommunications in the last five years.

Electromagnetics is one of the fundamental disciplines of electronic engineering.

Dealing with digital filtering methods for 1-D and 2-D signals, this book provides the theoretical background in signal processing, covering topics such as the z-transform, Shannon sampling theorem and fast Fourier transform.

This user guide presents a popular smoothing tool with practical applications in machine learning, engineering, and statistics.

Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification.

An exciting new development has taken place in the digital era that has captured the imagination and talent of researchers around the globe - wavelet image compression.

Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information.

* Modeling - creating objects in three-dimensional space.

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures.

For upper-level undergraduate courses in deterministic and stochastic signals and system engineering An Integrative Approach to Signals, Systems and Inference Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability.

This compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature.

An important working resource for engineers and researchers involved in the design, development, and implementation of signal processing systems The last decade has seen a rapid expansion of the use of field programmable gate arrays (FPGAs) for a wide range of applications beyond traditional digital signal processing (DSP) systems.

This book presents a state-of-the art review of current perspectives on Communications and Multimedia Security.

This is a major reference work about the overlapping fields of television, cable and video.

Provides the fundamental principles and practical tools needed to design next-generation wireless networks that are both energy- and spectrum-efficient.

This volume contains the latest worldwide research results on formal description techniques applicable to telecommunications, covering their theoretical foundations, industrial applications and practical usage.

Shapes have been among man's fascinations from thestoneage to thespace age.

Get the key measurement, modeling, and analytical tools for developing energy-aware and efficient systems and applications with this practical guide.

Sound, devoid of meaning, would not matter to us.

Focuses on practical application of spectral analysis of time series, with examples from environmental, engineering and physical sciences.

Digital image processing, originally established to analyze and improve lunar images, is rapidly growing into a wealth of new appli- cations, due to the enormous technical progress made in computer engineering.

Mobile computing is one of the biggest issues of computer technology, science and industry today.

A large international conference, Intelligent Systems and Computer Engineering, was held in Hong Kong, March 21-23, 2007, under the International MultiConf- ence of Engineers and Computer Scientists (IMECS) 2007.

An essential guide to the background, design, and application of common-mode filtering structures in modern high-speed differential communication links Written by a team of experts in the field, Electromagnetic Bandgap (EBG) Structures explores the practical electromagnetic bandgap based common mode filters for power integrity applications and covers the theoretical and practical design approaches for common mode filtering in high-speed printed circuit boards, especially for boards in high data-rate systems.

Speech Recognition has a long history of being one of the difficult problems in Artificial Intelligence and Computer Science.

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This book offers a rigorous mathematical analysis of fuzzy geometrical ideas.

A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods.

The pioneers of Flash-OFDM present OFDMA from first principles, enabling readers to apply theory to practice and understand mobile broadband.

This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application.

NTMS'2007 is the first IFIP International Conference on New Technologies, Mobility and Security that was held from May 2 to May 4, 2007 in Paris, France.

This book provides a comprehensive survey of the pharmacokinetic models used for the quantitative interpretation of contrast-enhanced imaging.

Modern Antennas, 2nd edition provides a complete and rigorous treatment of the theory and practice of modern antenna design and use.

This book provides an in-depth exposition of spin-stand microscopy of hard disk data which is a new technique recently developed and extensively tested by the authors of the book.

This book discusses the computational geometry, topology and physics of digital images and video frame sequences.

Digital Design of Signal Processing Systems discusses a spectrum of architectures and methods for effective implementation of algorithms in hardware (HW).

Synchronization is one of the important issues in digital system design.

This is not a dictionary - and nor is it an encyclopedia.

Human Factors and Voice Interactive Systems highlights the importance of human factors in speech technologies and presents and demonstrates the use of human factors, principles, methods, techniques, and tools in the design of speech-enabled applications.

The only integrative approach to chaos and random fractal theory Chaos and random fractal theory are two of the most important theories developed for data analysis.

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications.