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Time-Frequency Signal Analysis and Processing: A Comprehensive Reference (Eurasip and Academic Press Series in Signal and Image Processing)
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About Time-Frequency Signal Analysis And Processing: A
Product Description Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insights into how to use TFSAP methods to develop and implement the engineering application systems they require. New to this edition: New sections on Efficient and Fast Algorithms; a "Getting Started" chapter enabling readers to start using the algorithms on simulated and real examples with the TFSAP toolbox, compare the results with the ones presented in the book and then insert the algorithms in their own applications and adapt them as needed. Two new chapters and twenty three new sections, including updated references. New topics including: efficient algorithms for optimal TFDs (with source code), the enhanced spectrogram, time-frequency modelling, more mathematical foundations, the relationships between QTFDs and Wavelet Transforms, new advanced applications such as cognitive radio, watermarking, noise reduction in the time-frequency domain, algorithms for Time-Frequency Image Processing, and Time-Frequency applications in neuroscience (new chapter). Review A unique reference on Time-Frequency Signal Analysis and Processing, now updated with a strong emphasis on developing algorithms for advanced applications. From the Back Cover Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insight into how to use TFSAP methods to develop the engineering application systems they are looking to implement. New to this edition: New sections on Efficient Fast Algorithms and a section "Getting Started" which allows users to start using the algorithms on simulated and real examples, compare the results presented in the book and then insert the algorithms in their own application and adapt as needed Two new chapters, twenty three new sections, including the latest references New topics in this edition include: Efficient algorithms (with source code), the EMD, the S transform, time-frequency modelling, more mathematical foundations, relationship between QTFDs and Wavelet Transforms; new advanced applications such as cognitive radio; watermarking; noise reduction in the time-frequency domain; a time-frequency approach for spike detection; algorithms for Time-Frequency Image Processing; a full new chapter dedicated to Time-Frequency applications in neuroscience; a practical new chapter to help new users get started. Key features: A comprehensive tutorial introduction to Time-Frequency Signal Analysis and Processing TFSAP, accessible to anyone who has taken a first course in signals and systems Key theory and algorithms are concisely presented by some of the leading authorities on the respective topics Applications written by leading researchers showing how to use TFSAP methods About the Author Boualem Boashash (IEEE Fellow '99') is a Scholar, Professor and Senior Academic with experience in 5 leading Universities in France and Australia and 2 universities in the Middle-East. He has published over 500 technical publications, including over 100 journal papers, 3 books and 3 text-books covering Engineering, Applied Mathematics and Medicine. He was an early pioneer of the field of Time–Frequency Signal Processing and he is currently working on the further development of time-frequency theory and medical applications covering mental health and neurosciences with focus on newborn EEG analysis as well as ECG, HRV and fetal movements for improving health outcomes. Among many initiatives, he founded ISSPA
