New PDF release: Adaptive Signal Processing: Theory and Applications

By Thomas S. Alexander

ISBN-10: 1461249783

ISBN-13: 9781461249788

ISBN-10: 1461293820

ISBN-13: 9781461293828

The construction of the textual content fairly started in 1976 with the writer being concerned with a bunch of researchers at Stanford college and the Naval Ocean structures heart, San Diego. at the moment, adaptive thoughts have been extra laboratory (and psychological) curiosities than the approved and pervasive different types of sign processing that they've develop into. Over the lasl 10 years, adaptive filters became common parts in telephony, facts communications, and sign detection and monitoring platforms. Their use and client attractiveness will definitely in simple terms bring up sooner or later. The mathematical rules underlying adaptive sign processing have been firstly interesting and have been my first adventure in seeing utilized arithmetic paintings for a paycheck. given that that point, the applying of much more complicated mathematical ideas have stored the world of adaptive sign processing as intriguing as these preliminary days. The textual content seeks to be a bridge among the open literature within the specialist journals, that is frequently relatively centred, concise, and complex, and the graduate lecture room and examine setting the place underlying ideas are usually extra important.

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Extra resources for Adaptive Signal Processing: Theory and Applications

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6). 6) is of more theoretical than practical interest. 6). Since this iterative procedure is the basis for many currently used adaptive signal-processing techniques, the implications of the method of steepest descent will be explored in detail in this chapter. Steepest descent will be seen to lead directly to the popular least mean squares (LMS) adaptive algorithm, which has been widely implemented in actual systems. While the method of steepest descent itself is rarely used in actual adaptive signal processing systems, approximations to it are quite frequently implemented.

Other approaches to this derivation may be found in Proakis [3] and Atal and Hanauer [4]. One application of Durbin's algorithm might indeed be the computation of the optimum transversal filter coefficients. However, a set of alternative parameters called the reflection coefficients result as a natural consequence of Durbin's algorithm. These reflection coefficients may be used in an alternative linear prediction filter structure known as the lattice, which, in some applications, has distinct advantages over the transversal form.

5), which was based upon a geometrical consideration of the MSE surface. Thus, the normal equations have been alternatively derived from the mathematical perspective of fulfilling the orthogonality conditions. The same equations were previously produced by fulfilling the geometrical requirements at the minimum of the error surface. In later chapters, both mathematical and geometrical approaches will often be used in combination to investigate the same problem. Each approach complements the other and often gives insight not immediately obvious from the consideration of only a single approach.

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Adaptive Signal Processing: Theory and Applications by Thomas S. Alexander


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