Signal Processing

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Signals and Systems: A MATLAB® Integrated Approach

Signals and Systems: A MATLAB® Integrated Approach

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Oktay Alkin

March 18, 2014

Drawing on the author’s 25+ years of teaching experience, Signals and Systems: A MATLAB® Integrated Approach presents a novel and comprehensive approach to understanding signals and systems theory. Many texts use MATLAB® as a computational tool, but Alkin’s text employs MATLAB both computation...

Image and Video Compression: Fundamentals, Techniques, and Applications

Image and Video Compression: Fundamentals, Techniques, and Applications

Madhuri A. Joshi, Mehul S. Raval, Yogesh H. Dandawate, Kalyani R. Joshi, Shilpa P. Metkar

November 17, 2014

Image and video signals require large transmission bandwidth and storage, leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus, efficient image and video compression algorithms play a significant role in the storage and transmission of data. Image...

Signal Processing: A Mathematical Approach, Second Edition

Signal Processing: A Mathematical Approach, Second Edition

Charles L. Byrne

November 12, 2014

Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of...

Audio Effects: Theory, Implementation and Application

Audio Effects: Theory, Implementation and Application

Joshua D. Reiss, Andrew McPherson

October 23, 2014

Audio Effects: Theory, Implementation and Application explores digital audio effects relevant to audio signal processing and music informatics. It supplies fundamental background information on digital signal processing, focusing on audio-specific aspects that constitute the building block on which...

Regularization, Optimization, Kernels, and Support Vector Machines

Regularization, Optimization, Kernels, and Support Vector Machines

Johan A.K. Suykens, Marco Signoretto, Andreas Argyriou

October 23, 2014

Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and...

Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB®

Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB®

Alexander D. Poularikas

September 26, 2014

Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® covers the core concepts of this important field, focusing on a vital part of the...

Essential Principles of Image Sensors

Essential Principles of Image Sensors

Takao Kuroda

August 12, 2014

Providing a succinct introduction to the systemization, noise sources, and signal processes of image sensor technology, Essential Principles of Image Sensors discusses image information and its four factors: space, light intensity, wavelength, and time. Featuring clarifying and insightful...

Compressive Sensing for Urban Radar

Compressive Sensing for Urban Radar

Moeness Amin

August 07, 2014

With the emergence of compressive sensing and sparse signal reconstruction, approaches to urban radar have shifted toward relaxed constraints on signal sampling schemes in time and space, and to effectively address logistic difficulties in data acquisition. Traditionally, these challenges have...

Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications

Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications

Feng Wu

July 25, 2014

Visual information is one of the richest and most bandwidth-consuming modes of communication. To meet the requirements of emerging applications, powerful data compression and transmission techniques are required to achieve highly efficient communication, even in the presence of growing...

Sinusoids: Theory and Technological Applications

Sinusoids: Theory and Technological Applications

Prem K. Kythe

July 08, 2014

A Complete Treatment of Current Research Topics in Fourier Transforms and Sinusoids Sinusoids: Theory and Technological Applications explains how sinusoids and Fourier transforms are used in a variety of application areas, including signal processing, GPS, optics, x-ray crystallography,...

Signals and Systems: A MATLAB® Integrated Approach

Signals and Systems: A MATLAB® Integrated Approach

Oktay Alkin

March 18, 2014

Drawing on the author’s 25+ years of teaching experience, Signals and Systems: A MATLAB® Integrated Approach presents a novel and comprehensive approach to understanding signals and systems theory. Many texts use MATLAB® as a computational tool, but Alkin’s text employs MATLAB both computationally...

MIMO Power Line Communications: Narrow and Broadband Standards, EMC, and Advanced Processing

MIMO Power Line Communications: Narrow and Broadband Standards, EMC, and Advanced Processing

Lars Torsten Berger, Andreas Schwager, Pascal Pagani, Daniel Schneider

February 18, 2014

One of the first publications of its kind in the exciting field of multiple input multiple output (MIMO) power line communications (PLC), MIMO Power Line Communications: Narrow and Broadband Standards, EMC, and Advanced Processing contains contributions from experts in industry and academia, making...

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data

Haiping Lu, Konstantinos N. Plataniotis, Anastasios Venetsanopoulos

December 11, 2013

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient...

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