{"product_id":"blind-equalization-and-system-identification-batch-processing-algorithms-performance-and-applications-9781846280221","title":"Blind Equalization and System Identification: Batch Processing Algorithms, Performance and Applications","description":"\u003cp\u003e • Author(s): Chong-Yung Chi\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Electrical\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eDiscrete-time signal processing has had a momentous impact on advances in engineering and science over recent decades. The rapid progress of digital and mixed-signal integrated circuits in processing speed, functionality and cost-effectiveness has led to their ubiquitous employment in signal processing and transmission in diverse milieux.\u003c\/p\u003e \u003cp\u003eThe absence of training or pilot signals from many kinds of transmission - in, for example, speech analysis, seismic exploration and texture image analysis - necessitates the widespread use of blind equalization and system identification. There have been a great many algorithms developed for these purposes, working with one- or two-dimensional (2-d) signals and with single-input single-output (SISO) or multiple-input multiple-output (MIMO), real or complex systems. It is now time for a unified treatment of this subject, pointing out the common characteristics and the sometimes close relations of these algorithms as well as learning from their different perspectives. \u003cem\u003eBlind Equalization and System Identification\u003c\/em\u003e provides such a unified treatment presenting theory, performance analysis, simulation, implementation and applications.\u003c\/p\u003e \u003cp\u003eTopics covered include: \u003c\/p\u003e \u003cp\u003e- SISO, MIMO and 2-d non-blind equalization (deconvolution) algorithms; \u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e- SISO, MIMO and 2-d blind equalization (deconvolution) algorithms; \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e- SISO, MIMO and 2-d blind system identification algorithms; \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e- algorithm analyses and improvements; \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e \u003cp\u003e- applications of SISO, MIMO and 2-d blind equalization\/identification algorithms. \u003c\/p\u003e\u003cp\u003eEach chapter is completed by exercises and computer assignments designed to further understanding and to give practical experience with the algorithms discussed.\u003c\/p\u003e \u003cp\u003eThis is a textbook for graduate-level courses in discrete-time random processes, statistical signal processing, and blind equalization and system identification. It contains material which will also interest researchers and practicing engineers working in digital communications, source separation, speech processing, image processing, seismic exploration, sonar, radar and other, similar applications.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Paperback","offer_id":45274389938327,"sku":"9781846280221","price":3672.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781846280221.webp?v=1769279783","url":"https:\/\/atlanticbooks.com\/products\/blind-equalization-and-system-identification-batch-processing-algorithms-performance-and-applications-9781846280221","provider":"Atlantic Books","version":"1.0","type":"link"}