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Titlebook: Adaptive Nonlinear System Identification; The Volterra and Wie Tokunbo Ogunfunmi Book 2007 Springer-Verlag US 2007 Adaptive Filters.Filter.

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樓主
發(fā)表于 2025-3-21 17:38:26 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Adaptive Nonlinear System Identification
期刊簡稱The Volterra and Wie
影響因子2023Tokunbo Ogunfunmi
視頻videohttp://file.papertrans.cn/145/144715/144715.mp4
發(fā)行地址The focus is on the Volterra and Wiener modeling approaches, which have become very popular in signal processing circles
學(xué)科分類Signals and Communication Technology
圖書封面Titlebook: Adaptive Nonlinear System Identification; The Volterra and Wie Tokunbo Ogunfunmi Book 2007 Springer-Verlag US 2007 Adaptive Filters.Filter.
影響因子.Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches. introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials....After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications. ...Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches. is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processin
Pindex Book 2007
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發(fā)表于 2025-3-21 22:03:23 | 只看該作者
https://doi.org/10.1007/978-3-8350-9278-5 too high) even for low-order non-linear filters such as second-order. (2) The convergence rate is typically slow especially for stochastic-gradienttype algorithms. (3) They sometimes do not converge or lead to high misadjustment. (4) Their performance is not very good for non-white and/or non-Gaussian inputs.
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發(fā)表于 2025-3-22 01:10:03 | 只看該作者
Book 2007aptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear syst
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1860-4862 System Identification: The Volterra and Wiener Model Approaches. introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-unde
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Introduction to Nonlinear Systems,. Thus, in a little more than three years, Spain managed to overcome nearly forty years of dictatorship by carrying out an ‘ideal type of a negotiated transition’, which set the conditions for the following ‘successful and relatively unproblematic consolidation of democracy’.. In comparison with oth
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