Research and Markets: Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications.DUBLIN, Ireland -- Research and Markets (http://www.researchandmarkets.com/reports/c74308) has announced the addition of Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications to their offering. Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing See DSP. Digital Signal Processing - (DSP) Computer manipulation of analog signals (commonly sound or image) which have been converted to digital form (sampled). (DSP (1) (Digital Signal Processor) A special-purpose CPU used for digital signal processing applications (see definition #2 below). It provides ultra-fast instruction sequences, such as shift and add, and multiply and add, which are commonly used in math-intensive ). The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data forecasting, artificial intelligence, decision making, control systems and search engines. This book is organised in to three major parts making it a coherent and structured presentation of the theory and applications of digital signal processing. A range of important topics are covered in basic signal processing, model-based statistical signal processing Statistical signal processing is an area of signal processing that treats signals as stochastic processes, dealing with their statistical properties (e.g., mean, covariance, etc.). and their applications. The aim of this book is to provide a coherent and structured presentation of the theory and applications of statistical signal processing in three sections: Part 1: Basic Digital Signal Processing gives an introduction to the topic, discussing sampling and quantization (1) The division of a range of values into a single number, code or classification. For example, class A is 0 to 999, class B is 1000 to 9999 and class C is 10000 and above. (2) In analog to digital conversion, the assignment of a number to the amplitude of a wave. , Fourier analysis and synthesis, Z-transform, and digital filters. Part 2: Model-based Signal Processing covers probability and information models, Bayesian inference, Wiener filter, adaptive filters, linear prediction hidden Markov models and independent component analysis. Part 3: Applications of Signal Processing in Speech, Music and Telecommunications explains the topics of speech and music processing, echo cancellation, deconvolution In mathematics, deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data.[1] The concept of deconvolution is widely used in the techniques of signal processing and image processing. and channel equalization In communications, techniques used to reduce distortion and compensate for signal loss (attenuation) over long distances. , and mobile communication signal processing. - Covers music signal processing, explains the anatomy and psychoacoustics Psychoacoustics All of the psychological interactions between humans (and animals) and the world of sound. It encompasses all studies of the perception of sound, as well as the production of speech. See Hearing (human), Speech of hearing and the design of MP3 music coder - Examines speech processing technology including speech models, speech coding for mobile phones and speech recognition - Covers single-input and multiple-inputs denoising methods, bandwidth extension and the recovery of lost speech packets in applications such as voice over IP (VoIP) - Illustrated throughout, including numerous solved problems, Matlab experiments and demonstrations - Companion website features Matlab and C++ programs with electronic copies of all figures. This book is ideal for researchers, postgraduates and senior undergraduates in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be a valuable text to professional engineers in telecommunications and audio and signal processing industries. About the author: Saeed Vaseghi is Professor of Communications and Signal Processing at Brunel Universitys Department of Electronics and Computer Engineering and is Group Leader for the Communications & Multimedia Signal Processing Group. Previously, Saeed obtained a first in Electrical and Electronics Engineering from Newcastle University, and a PhD in Digital Signal Processing from Cambridge University. His PhD in noisy signal restoration led to establishment of CEDAR, the world's leading system for restoration of audio signals. Saeed also held a British Telecom lectureship lec·ture·ship n. 1. The status or position of a lecturer. 2. An endowment or foundation supporting a series or course of lectures. [Alteration of lecturership. at UEA UEA University of East Anglia (UK) UEA Universala Esperanto-Asocio (World Esperanto Association) UEA Utah Education Association UEA Urban Exploration Alberta UEA United Earth Alliance Norwich, and a readership at Queen's University of Belfast before his move to Brunel Content Outline: Preface Acknowledgement Symbols Abbreviations Part I Basic Digital Signal Processing 1 Introduction 2 Fourier Analysis and Synthesis 3 z-Transform 4 Digital Filters 5 Sampling and Quantisation Noun 1. quantisation - the act of dividing into quanta or expressing in terms of quantum theory quantization division - the act or process of dividing Part II Model-Based Signal Processing 6 Information Theory and Probability Models 7 Bayesian Inference 8 Least Square Error, Wiener-Kolmogorov Filters 9 Adaptive Filters: Kalman, RLS Restless legs syndrome (RLS) A disorder in which the patient experiences crawling, aching, or other disagreeable sensations in the calves that can be relieved by movement. RLS is a frequent cause of difficulty falling asleep at night. , LMS 10 Linear Prediction Models 11 Hidden Markov Models 12 Eigenvector (mathematics) eigenvector - A vector which, when acted on by a particular linear transformation, produces a scalar multiple of the original vector. The scalar in question is called the eigenvalue corresponding to this eigenvector. Analysis, Principal Component Analysis and Independent Component Analysis Part III Applications of Digital Signal Processing to Speech, Music and Telecommunications 13 Music Signal Processing and Auditory Perception 14 Speech Processing 15 Speech Enhancement 16 Echo Cancellation 17 Channel Equalisation and Blind Deconvolution 18 Signal Processing in Mobile Communication Index For more information visit http://www.researchandmarkets.com/reports/c74308 |
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