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Titlebook: Microphone Arrays; Jacob Benesty,Gongping Huang,Ningning Pan Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive li

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發(fā)表于 2025-3-21 17:16:08 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Microphone Arrays
編輯Jacob Benesty,Gongping Huang,Ningning Pan
視頻videohttp://file.papertrans.cn/634/633375/633375.mp4
概述Presents the benefits of microphone arrays over single sensors from a signal enhancement / spatial filtering perspective.Includes algorithms for dimensionality reduction and fixed and adaptive beamfor
叢書名稱Springer Topics in Signal Processing
圖書封面Titlebook: Microphone Arrays;  Jacob Benesty,Gongping Huang,Ningning Pan Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive li
描述.This book explains the motivation for using microphone arrays as opposed to using a single sensor for sound acquisition. The book then goes on to summarize the most useful ideas, concepts, results, and new algorithms therein. The material presented in this work includes analysis of the advantages of using microphone arrays, including dimensionality reduction to remove the redundancy while preserving the variability of the array signals using the principal component analysis (PCA). The authors also discuss benefits such as beamforming with low-rank approximations, fixed, adaptive, and robust distortionless beamforming, differential beamforming, and a new form of binaural beamforming that takes advantage of both beamforming and human binaural hearing properties to improve speech intelligibility. The book makes the microphone array signal processing theory and applications available in a complete and self-contained text. The authors attempt to explain the main ideas in a clear and rigorous way so that the reader can easily capture the potentials, opportunities, challenges, and limitations of microphone array signal processing. This book is written for those who work on the topics of
出版日期Book 2024
關(guān)鍵詞dimensionality reduction; Microphone arrays; distortionless beamforming; low-rank beamforming; binaural
版次1
doihttps://doi.org/10.1007/978-3-031-36974-2
isbn_softcover978-3-031-36976-6
isbn_ebook978-3-031-36974-2Series ISSN 1866-2609 Series E-ISSN 1866-2617
issn_series 1866-2609
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-22 01:30:28 | 只看該作者
Jacob Benesty,Gongping Huang,Ningning PanPresents the benefits of microphone arrays over single sensors from a signal enhancement / spatial filtering perspective.Includes algorithms for dimensionality reduction and fixed and adaptive beamfor
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發(fā)表于 2025-3-22 08:12:24 | 只看該作者
978-3-031-36976-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-22 09:29:35 | 只看該作者
Microphone Arrays978-3-031-36974-2Series ISSN 1866-2609 Series E-ISSN 1866-2617
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發(fā)表于 2025-3-22 13:53:28 | 只看該作者
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發(fā)表于 2025-3-22 17:43:30 | 只看該作者
Adaptive Noise Cancellation,In some applications, it may be more convenient to find a noise reference, which can then be used to adaptively cancel the additive noise at microphones. This chapter is concerned with this problem. Furthermore, as it will be explained, adaptive noise cancellation gives another insightful perspective of distortionless adaptive beamforming.
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發(fā)表于 2025-3-23 00:38:15 | 只看該作者
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發(fā)表于 2025-3-23 01:38:59 | 只看該作者
Principal Component Analysis in Noise Reduction and Beamforming,bjective of PCA is the reduction of the dimension of a random signal vector from . to ., where ., with little loss of the useful information. It does so by preserving the variability of the signal as much as possible, where the new variables are uncorrelated. In this chapter, we show how PCA can be applied to noise reduction and beamforming.
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發(fā)表于 2025-3-23 09:13:36 | 只看該作者
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