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Titlebook: Adaptive Filtering; Algorithms and Pract Paulo Sergio Ramirez Diniz Book 1997 Springer Science+Business Media New York 1997 Adaptive Filter

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期刊全稱Adaptive Filtering
期刊簡(jiǎn)稱Algorithms and Pract
影響因子2023Paulo Sergio Ramirez Diniz
視頻videohttp://file.papertrans.cn/145/144642/144642.mp4
學(xué)科分類The Springer International Series in Engineering and Computer Science
圖書(shū)封面Titlebook: Adaptive Filtering; Algorithms and Pract Paulo Sergio Ramirez Diniz Book 1997 Springer Science+Business Media New York 1997 Adaptive Filter
影響因子The field of Digital Signal Processing has developed so fast in the last two decades that it can be found in the graduate and undergraduate programs of most universities. This development is related to the growing available techno- logies for implementing digital signal processing algorithms. The tremendous growth of development in the digital signal processing area has turned some of its specialized areas into fields themselves. If accurate information of the signals to be processed is available, the designer can easily choose the most appropriate algorithm to process the signal. When dealing with signals whose statistical properties are unknown, fixed algorithms do not process these signals efficiently. The solution is to use an adaptive filter that automatically changes its characteristics by optimizing the internal parameters. The adaptive filtering algorithms are essential in many statistical signal processing applications. Although the field of adaptive signal processing has been subject of research for over three decades, it was in the eighties that a major growth occurred in research and applications. Two main reasons can be credited to this growth, the availability of impl
Pindex Book 1997
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Fazit Aus Sicht der Herausgeberalization are very attractive because they allow modular implementation and require a reduced number of arithmetic operations (of order .) [.]–[.]. As a consequence, the lattice recursive least-squares (LRLS) algorithms are considered fast implementations of the RLS problem.
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https://doi.org/10.1007/978-1-4419-8660-3Adaptive Filter; Matlab; Signal; development; digital signal processing; filter; filtering; filters; informa
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