Fundamentals of Spherical Array Processing: Springer Topics in Signal Processing, cartea 16
Autor Boaz Rafaelyen Limba Engleză Paperback – feb 2019
The first two chapters provide the reader with the necessary mathematical and physical background, including an introduction to the spherical Fourier transform and the formulation of plane-wave sound fields in the spherical harmonic domain. In turn, the third chapter covers the theory of spatial sampling, employed when selecting the positions of microphones to sample sound pressure functions in space. Subsequent chapters highlight various spherical array configurations, including the popular rigid-sphere-based configuration. Beamforming (spatial filtering) in the spherical harmonics domain, including axis-symmetric beamforming, and the performance measures of directivity index and white noise gain are introduced, and a range of optimal beamformers for spherical arrays, including those that achieve maximum directivity and maximum robustness are developed, along with the Dolph–Chebyshev beamformer. The final chapter discusses more advanced beamformers, such as MVDR (minimum variance distortionless response) and LCMV (linearly constrained minimum variance) types, which are tailored to the measured sound field.
Mathworks kindly distributes the Matlab sources for this book on https://www.mathworks.com/matlabcentral/fileexchange/68655-fundamentals-of-spherical-array-processing.
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Paperback (1) | 904.76 lei 43-57 zile | |
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Specificații
ISBN-13: 9783030076115
ISBN-10: 3030076113
Pagini: 193
Ilustrații: XII, 193 p. 76 illus., 27 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.3 kg
Ediția:Softcover reprint of the original 2nd ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Springer Topics in Signal Processing
Locul publicării:Cham, Switzerland
ISBN-10: 3030076113
Pagini: 193
Ilustrații: XII, 193 p. 76 illus., 27 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.3 kg
Ediția:Softcover reprint of the original 2nd ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Springer Topics in Signal Processing
Locul publicării:Cham, Switzerland
Cuprins
Mathematical background.- Acoustical Background.-Sampling the Sphere.- Spherical array configurations.- Spherical Array Beamforming.- Optimal beam pattern design.- Beamforming with noise minimization.
Recenzii
“The book is written mainly for graduate students and researchers in physical acoustics and engineering, although many parts would be suitable for advanced undergraduates.” (Edward S. Krebes, The Leading Edge, Vol. 38 (11), November, 2019)
Textul de pe ultima copertă
This book provides a comprehensive introduction to the theory and practice of spherical microphone arrays, and was written for graduate students, researchers and engineers who work with spherical microphone arrays in a wide range of applications. The new edition includes additions and modifications, and references supplementary Matlab code to provide the reader with a straightforward start for own implementations. The book is also accompanied by a Matlab manual, which explains how to implement the examples and simulations presented in the book.
The first two chapters provide the reader with the necessary mathematical and physical background, including an introduction to the spherical Fourier transform and the formulation of plane-wave sound fields in the spherical harmonic domain. In turn, the third chapter covers the theory of spatial sampling, employed when selecting the positions of microphones to sample sound pressure functions in space. Subsequent chapters highlight various spherical array configurations, including the popular rigid-sphere-based configuration. Beamforming (spatial filtering) in the spherical harmonics domain, including axis-symmetric beamforming, and the performance measures of directivity index and white noise gain are introduced, and a range of optimal beamformers for spherical arrays, including those that achieve maximum directivity and maximum robustness are developed, along with the Dolph–Chebyshev beamformer. The final chapter discusses more advanced beamformers, such as MVDR (minimum variance distortionless response) and LCMV (linearly constrained minimum variance) types, which are tailored to the measured sound field.
The first two chapters provide the reader with the necessary mathematical and physical background, including an introduction to the spherical Fourier transform and the formulation of plane-wave sound fields in the spherical harmonic domain. In turn, the third chapter covers the theory of spatial sampling, employed when selecting the positions of microphones to sample sound pressure functions in space. Subsequent chapters highlight various spherical array configurations, including the popular rigid-sphere-based configuration. Beamforming (spatial filtering) in the spherical harmonics domain, including axis-symmetric beamforming, and the performance measures of directivity index and white noise gain are introduced, and a range of optimal beamformers for spherical arrays, including those that achieve maximum directivity and maximum robustness are developed, along with the Dolph–Chebyshev beamformer. The final chapter discusses more advanced beamformers, such as MVDR (minimum variance distortionless response) and LCMV (linearly constrained minimum variance) types, which are tailored to the measured sound field.
Caracteristici
Presents cutting-edge theory and algorithms for spherical microphone arrays, including implementation examples and simulations with Matlab Relevant for a broad range of applications in audio and acoustics, including speech communication, music recording, room acoustics, acoustic holography, virtual acoustics, and binaural sound reproduction Is also relevant for other areas such as image processing and geodesy