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A key task of engineers is to design and analyse systems; however, they often have to do this without knowing a system's parameters. BSS is a very important area in signal processing as it enables engineers to derive the unknown inputs of a system from its known outputs. It also enables the separation of a set of signals from mixed set of signals. This is particularly important in telecommunications and biomedical engineering but is also key in speech, acoustic, audio and music processing and scientific data analysis. It is, therefore, a method that has wide applicability and is a very useful

Blind source separation. --- Source separation (Signal processing) --- Separation, Signal --- Separation, Source (Signal processing) --- Signal separation --- Signal processing --- Blind signal separation --- BSS (Blind source separation)

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Signal processing --- Synthetic aperture radar. --- Source separation (Signal processing) --- Digital techniques. --- Digital signal processing --- Digital communications --- Digital electronics --- Separation, Signal --- Separation, Source (Signal processing) --- Signal separation --- SAR (Synthetic aperture radar) --- Coherent radar

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Simon Grimm examines new multi-microphone signal processing strategies that aim to achieve noise reduction and dereverberation. Therefore, narrow-band signal enhancement approaches are combined with broad-band processing in terms of directivity based beamforming. Previously introduced formulations of the multichannel Wiener filter rely on the second order statistics of the speech and noise signals. The author analyses how additional knowledge about the location of a speaker as well as the microphone arrangement can be used to achieve further noise reduction and dereverberation. The Content Directivity Based Reference for the Generalized Multichannel Wiener Filter Reference for the Binaural Multichannel Wiener Filter Wind Noise Reduction for a Closely Spaced Microphone Array Background Noise Simulation based on MIMO Equalization The Target Groups Lecturers and Students in the field of Speech Signal Processing Practitioners of Speech Signal Processing and Noise Reduction The Author Simon Grimm was a research assistant at the Institute of System Dynamics at the HTWG Konstanz, Germany, from October 2014 to March 2018. During his research period, he was working in the area of speech signal processing for multichannel microphone arrangements. He finished his Ph.D. in June 2018. Currently he is employed as a signal processing engineer at a German audio equipment manufacturer.

Computer engineering. --- Engineering mathematics. --- Information systems. --- Electrical Engineering. --- Mathematical and Computational Engineering. --- Information Systems and Communication Service. --- Beamforming. --- Source separation (Signal processing) --- Separation, Signal --- Separation, Source (Signal processing) --- Signal separation --- Signal processing --- Spatial filtering (Signal processing) --- Electrical engineering. --- Applied mathematics. --- Computers. --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Electric engineering

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This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sources are presented. The book further focuses on the non-negativity based methods, the time-frequency analysis based methods, and the pre-coding based methods, respectively.

Engineering. --- Signal, Image and Speech Processing. --- Communications Engineering, Networks. --- Circuits and Systems. --- Telecommunication. --- Systems engineering. --- Ingénierie --- Télécommunications --- Ingénierie des systèmes --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Electrical Engineering --- Telecommunications --- Applied Physics --- Blind source separation. --- Blind signal separation --- BSS (Blind source separation) --- Electrical engineering. --- Electronic circuits. --- Source separation (Signal processing) --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Communication --- Information theory --- Telecommuting --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Design and construction --- Signal processing. --- Image processing. --- Speech processing systems. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Electric engineering --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Computational linguistics --- Electronic systems --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers

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"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong University in the areas of speech signal processing, underwater signals, image feature extraction, data compression, and the like are discussed. This book will be of particular interest to advanced undergraduate students, graduate students, university instructors and research scientists in related disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University.

Blind source separation. --- Signal processing -- Digital techniques. --- Signal processing --- Blind source separation --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Telecommunications --- Electrical Engineering --- Applied Physics --- Digital techniques. --- Digital signal processing --- Blind signal separation --- BSS (Blind source separation) --- Engineering. --- Image processing. --- Information theory. --- Electrical engineering. --- Signal, Image and Speech Processing. --- Information and Communication, Circuits. --- Communications Engineering, Networks. --- Image Processing and Computer Vision. --- Digital communications --- Digital electronics --- Source separation (Signal processing) --- Mathematics. --- Telecommunication. --- Computer vision. --- Math --- Science --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Communication --- Information theory --- Telecommuting --- Signal processing. --- Speech processing systems. --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Electric engineering --- Engineering --- Communication theory --- Cybernetics --- Computational linguistics --- Electronic systems --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Optical equipment