Digital Communications Review

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Digital Communications ReviewMany of the reviewers criticized the book, largely because of it being difficult to read. However, the real question a potential reader should ask him/herself is whether the book is intended as a reference manual or as a textbook for learning new material. As a textbook, the pace is too fast, there are few examples, and the level is too complicated for the novice reader. However, as a reference manual, for the practicing engineer or researcher, this book encompasses a vast span of material and is extremely useful. The potential buyer must determine whether the book is intended as a textbook or reference manual. As a reference manual the book deserves the full five stars, but as a textbook, two stars are more than enough.Digital Communications Overview

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Statistical Signal Processing for Neuroscience and Neurotechnology Review

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Statistical Signal Processing for Neuroscience and Neurotechnology ReviewCapturing the signals from neurons is a very complex undertaking, as they must be gleaned from a great deal of extraneous data. There is the low-level random background noise generated by the natural transient changes in concentrations of ions and there are the pseudorandom oscillations of other physiological activity such as blood flow and the resultant movement of nutrients. The alterations of electrical potentials based on the actions of neurons must be extracted from all of this before any attempt can be made to study the phenomena.
The algorithms used to obtain this information are based on statistical models and are presented in detail in this book. Understanding those models requires a great deal of knowledge of mathematics, with an emphasis on statistics. The statistical models are based on calculus, so exposure to advanced statistical techniques is necessary. A large number of graphs illustrating the behavior of the models as well as some depicting actual collected data are included. Natural consequences of the work, such as the development of artificial limbs that respond to neuron activity are also covered.
One of the major tools now used in the advancement of knowledge in many areas of science is the ability to mine the significant data from an overall stream of data, especially when that data is of secondary strength. The statistical techniques described here are used to extract the neural signals from everything else and are part of what is sure to be a revolution in prosthetics. This book is an excellent work in this area and some parts contain valuable information useful for computer scientists interested in machine cognitive models.
Statistical Signal Processing for Neuroscience and Neurotechnology Overview

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Adaptive Filtering: Algorithms and Practical Implementation Review

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Adaptive Filtering: Algorithms and Practical Implementation ReviewThe book by Prof. Diniz is indeed amongst the best on adaptive signal processing. Most of the fundamental concepts are well explained, suitable examples are given and practical applications are also discussed. The chapter on adaptive IIR filters is unique and still cannot be found in any other book. Moreover, solutions to the problems can be obtained by ftp, which is something very useful for students. Despite this is an excellent book (5 star), the price is ridiculous, as occurs with most titles from this publisher. If I were Prof. Diniz I would change from Kluwer Academic Publishers to a more competitive publisher.Adaptive Filtering: Algorithms and Practical Implementation Overview

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