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Theory and Applications of Spherical Microphone Array Processing by Daniel P. Ja

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Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN-13
9783319825250
Book Title
Theory and Applications of Spherical Microphone Array Processing
ISBN
9783319825250
Subject Area
Computers, Technology & Engineering, Science
Publication Name
Theory and Applications of Spherical Microphone Array Processing
Publisher
Springer International Publishing A&G
Item Length
9.3 in
Subject
Signals & Signal Processing, Speech & Audio Processing, Acoustics & Sound
Publication Year
2018
Series
Springer Topics in Signal Processing Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Emanuël A. P. Habets, Patrick A. Naylor, Daniel P. Jarrett
Item Weight
16 Oz
Item Width
6.1 in
Number of Pages
Xvi, 187 Pages

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3319825259
ISBN-13
9783319825250
eBay Product ID (ePID)
17038741718

Product Key Features

Number of Pages
Xvi, 187 Pages
Language
English
Publication Name
Theory and Applications of Spherical Microphone Array Processing
Publication Year
2018
Subject
Signals & Signal Processing, Speech & Audio Processing, Acoustics & Sound
Type
Textbook
Author
Emanuël A. P. Habets, Patrick A. Naylor, Daniel P. Jarrett
Subject Area
Computers, Technology & Engineering, Science
Series
Springer Topics in Signal Processing Ser.
Format
Trade Paperback

Dimensions

Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Series Volume Number
9
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
Introduction.- Theoretical Preliminaries of Acoustics.- Spatial Sampling and Signal Transformation.- Spherical Array Acoustic Impulse Response Simulation.- Acoustic Parameter Estimation.- Signal-Independent Array Processing.
Synopsis
This book presents the signal processing algorithms that have been developed to process the signals acquired by a spherical microphone array. Spherical microphone arrays can be used to capture the sound field in three dimensions and have received significant interest from researchers and audio engineers. Algorithms for spherical array processing are different to corresponding algorithms already known in the literature of linear and planar arrays because the spherical geometry can be exploited to great beneficial effect. The authors aim to advance the field of spherical array processing by helping those new to the field to study it efficiently and from a single source, as well as by offering a way for more experienced researchers and engineers to consolidate their understanding, adding either or both of breadth and depth. The level of the presentation corresponds to graduate studies at MSc and PhD level. This book begins with a presentation of some of the essential mathematical and physical theory relevant to spherical microphone arrays, and of an acoustic impulse response simulation method, which can be used to comprehensively evaluate spherical array processing algorithms in reverberant environments. The chapter on acoustic parameter estimation describes the way in which useful descriptions of acoustic scenes can be parameterized, and the signal processing algorithms that can be used to estimate the parameter values using spherical microphone arrays. Subsequent chapters exploit these parameters including in particular measures of direction-of-arrival and of diffuseness of a sound field. The array processing algorithms are then classified into two main classes, each described in a separate chapter. These are signal-dependent and signal-independent beamforming algorithms. Although signal-dependent beamforming algorithms are in theory able to provide better performance compared to the signal-independent algorithms, they are currently rarely used in practice. The main reason for this is that the statistical information required by these algorithms is difficult to estimate. In a subsequent chapter it is shown how the estimated acoustic parameters can be used in the design of signal-dependent beamforming algorithms. This final step closes, at least in part, the gap between theory and practice.
LC Classification Number
TK5102.9

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