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Adaptive Filtering - Theories and Applications, Lefteris Tyler


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Автор: Lefteris Tyler
Название:  Adaptive Filtering - Theories and Applications
ISBN: 9781681172071
Издательство: Gazelle Book Services
Классификация:
ISBN-10: 1681172070
Обложка/Формат: Hardback
Страницы: 300
Вес: 0.71 кг.
Дата издания: 01.04.2016
Серия: Engineering
Язык: English
Размер: 163 x 237 x 22
Ключевые слова: Electrical engineering
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Поставляется из: Англии
Описание: An adaptive filter is a computational device that iteratively models the relationship between the input and output signals of the filter. An adaptive filter self-adjusts the filter coefficients according to an adaptive algorithm. Over the past three decades, digital signal processors have made great advances in increasing speed and complexity, and reducing power consumption. As a result, real-time adaptive filtering algorithms are quickly becoming practical and essential for the future of communications, both wired and wireless. An adaptive filter designs itself based on the characteristics of the input signal to the filter and a signal that represents the desired behaviour of the filter on its input. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some applications because some parameters of the desired processing operation are not known in advance or are changing. The closed loop adaptive filter uses feedback in the form of an error signal to refine its transfer function. Adaptive filtering can be used to characterize unknown systems in time-variant environments. Commonly, the closed loop adaptive process involves the use of a cost function, which is a criterion for optimum performance of the filter, to feed an algorithm, which determines how to modify filter transfer function to minimize the cost on the next iteration. The most common cost function is the mean square of the error signal. This book, Adaptive Filtering - Theories and Applications, offers some theoretical approaches and practical applications in diverse areas that support increasing of adaptive systems. The book reflect the latest advances in this field; particularly an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years.

Adaptive Filtering

Автор: Diniz
Название: Adaptive Filtering
ISBN: 1461441056 ISBN-13(EAN): 9781461441052
Издательство: Springer
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Цена: 102480.00 T
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Описание: In its 4th edition, this book reviews basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, covering the main classes of adaptive filtering algorithms and using clear notation to facilitate implementation.

Adaptive Filtering

Автор: Poularikas
Название: Adaptive Filtering
ISBN: 1482253356 ISBN-13(EAN): 9781482253351
Издательство: Taylor&Francis
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Цена: 102080.00 T
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Описание:

Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(R) covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area--the least mean square (LMS) adaptive filter.

This largely self-contained text:

  • Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions
  • Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces
  • Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton's algorithm
  • Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples
  • Delivers a concise introduction to MATLAB(R), supplying problems, computer experiments, and more than 110 functions and script files

Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(R) clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems.


Adaptive Filtering

Автор: Paulo S R Diniz
Название: Adaptive Filtering
ISBN: 1461346606 ISBN-13(EAN): 9781461346609
Издательство: Springer
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Цена: 93160.00 T
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Описание: 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. If accurate information of the signals to be processed is available, the designer can easily choose the most appropriate algorithm to process the signal.

QRD-RLS Adaptive Filtering

Автор: JOSE APOLINARIO JR
Название: QRD-RLS Adaptive Filtering
ISBN: 1441935266 ISBN-13(EAN): 9781441935267
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book provides tools and knowledge in a simple way so that the reader is able to implement a particular QRD-RLS algorithm tailored for the application at hand. The book comprehensively compiles the research of more than a decade into a single publication.

Digital Filtering in One and Two Dimensions

Автор: M. Ahmadi; M. Azimi-Sadjadi; R. Gorgui-Naguib; R.
Название: Digital Filtering in One and Two Dimensions
ISBN: 1489909206 ISBN-13(EAN): 9781489909206
Издательство: Springer
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Цена: 174150.00 T
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Описание: This book has been conceived to extend the generally published work on one- and two-dimensional digital filters in order to include some of the more recently developed ideas.

Parametrizations in Control, Estimation and Filtering Problems: Accuracy Aspects

Автор: Michel Gevers; Gang Li
Название: Parametrizations in Control, Estimation and Filtering Problems: Accuracy Aspects
ISBN: 1447120418 ISBN-13(EAN): 9781447120414
Издательство: Springer
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Цена: 95770.00 T
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Описание: This book is all about finite wordlength errors in digital filters, con- trollers and estimators, and how to minimize the deleterious effects of these errors on the performance of these devices.

Smoothing, Filtering & Prediction: Estimating the Past, Present & Future

Автор: Jeremy Weissberg
Название: Smoothing, Filtering & Prediction: Estimating the Past, Present & Future
ISBN: 1681176068 ISBN-13(EAN): 9781681176062
Издательство: Gazelle Book Services
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Цена: 217350.00 T
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Описание: Smoothing is often used to reduce noise within an image or to produce a less pixelated image. Most smoothing methods are based on low pass filters. Smoothing is also usually based on a single value representing the image, such as the average value of the image or the middle (median) value. In image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points (presumably because of noise) are reduced, and points that are lower than the adjacent points are increased leading to a smoother signal. Smoothing may be used in two important ways that can aid in data analysis; by being able to extract more information from the data as long as the assumption of smoothing is reasonable and; by being able to provide analyses that are both flexible and robust. Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. This book describes the classical smoothing, filtering and prediction techniques together with some more recently developed embellishments for improving performance within applications. It aims to present the subject in an accessible way, so that it can serve as a practical guide for undergraduates and newcomers to the field.

Electricity Markets: Theories and Applications

Автор: Jeremy Lin
Название: Electricity Markets: Theories and Applications
ISBN: 1119179351 ISBN-13(EAN): 9781119179351
Издательство: Wiley
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Цена: 111880.00 T
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Описание:

A comprehensive resource that provides the basic concepts of electric power systems, microeconomics, and optimization techniques

Electricity Markets: Theories and Applications offers students and practitioners a clear understanding of the fundamental concepts of the economic theories, particularly microeconomic theories, as well as information on some advanced optimization methods of electricity markets. The authors--noted experts in the field--cover the basic drivers for the transformation of the electricity industry in both the United States and around the world and discuss the fundamentals of power system operation, electricity market design and structures, and electricity market operations.

The text also explores advanced topics of power system operations and electricity market design and structure including zonal versus nodal pricing, market performance and market power issues, transmission pricing, and the emerging problems electricity markets face in smart grid and micro-grid environments. The authors also examine system planning under the context of electricity market regime. They explain the new ways to solve problems with the tremendous amount of economic data related to power systems that is now available. This important resource:

  • Introduces fundamental economic concepts necessary to understand the operations and functions of electricity markets
  • Presents basic characteristics of power systems and physical laws governing operation
  • Includes mathematical optimization methods related to electricity markets and their applications to practical market clearing issues

Electricity Markets: Theories and Applications is an authoritative text that explores the basic concepts of the economic theories and key information on advanced optimization methods of electricity markets.



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