Digital Signal Processing Using the ARM?® Cortex?® - M4 essfull, Reay
Автор: Thomas Holton Название: Digital Signal Processing: Principles and Applications ISBN: 1108418449 ISBN-13(EAN): 9781108418447 Издательство: Cambridge Academ Рейтинг: Цена: 16474.00 р. Наличие на складе: Заказано в издательстве.
Описание: A comprehensive and mathematically accessible introduction to digital signal processing, with clear explanations of elementary principles, advanced topics, and applications. It features over 600 full-color figures, 200 worked examples, hundreds of end-of-chapter problems, and computational examples of DSP algorithms implemented in Matlab and C.
Автор: Anand, R. Название: Digital signal processing ISBN: 1683928024 ISBN-13(EAN): 9781683928027 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 8959.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed to cover the fundamental concepts of digital signal processing, this book introduces topics such as discrete-time signals, the z-transform, frequency analysis, discrete and fast Fourier transforms, digital filters, FIR, statistical DSP, applications, and more.
Автор: Hudak Paul Название: Haskell School of Music ISBN: 1108416756 ISBN-13(EAN): 9781108416757 Издательство: Cambridge Academ Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book teaches functional programming through creative applications in music and sound synthesis. Readers will learn the Haskell programming language and explore numerous ways to create music and design virtual instruments with concise, elegant code.
Описание: Multirate signal processing techniques are widely used in many areas of modern engineering such as communications, digital audio, measurements, image and signal processing, speech processing, and multimedia. This book covers basic and advanced approaches in the design and implementation of multirate filtering.
Автор: Viacheslav Karmalita Название: Digital Processing of Random Oscillations ISBN: 3110625008 ISBN-13(EAN): 9783110625004 Издательство: Walter de Gruyter Рейтинг: Цена: 16727.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book deals with the autoregressive method for digital processing of random oscillations. The method is based on a one-to-one transformation of the numeric factors of the Yule series model to linear elastic system characteristics. This parametric approach allowed to develop a formal processing procedure from the experimental data to obtain estimates of logarithmic decrement and natural frequency of random oscillations. A straightforward mathematical description of the procedure makes it possible to optimize a discretization of oscillation realizations providing efficient estimates. The derived analytical expressions for confidence intervals of estimates enable a priori evaluation of their accuracy. Experimental validation of the method is also provided. Statistical applications for the analysis of mechanical systems arise from the fact that the loads experienced by machineries and various structures often cannot be described by deterministic vibration theory. Therefore, a sufficient description of real oscillatory processes (vibrations) calls for the use of random functions. In engineering practice, the linear vibration theory (modeling phenomena by common linear differential equations) is generally used. This theory’s fundamental concepts such as natural frequency, oscillation decrement, resonance, etc. are credited for its wide use in different technical tasks. In technical applications two types of research tasks exist: direct and inverse. The former allows to determine stochastic characteristics of the system output X(t) resulting from a random process E(t) when the object model is considered known. The direct task enables to evaluate the effect of an operational environment on the designed object and to predict its operation under various loads. The inverse task is aimed at evaluating the object model on known processes E(t) and X(t), i.e. finding model (equations) factors. This task is usually met at the tests of prototypes to identify (or verify) its model experimentally. To characterize random processes a notion of "shaping dynamic system" is commonly used. This concept allows to consider the observing process as the output of a hypothetical system with the input being stationary Gauss-distributed ("white") noise. Therefore, the process may be exhaustively described in terms of parameters of that system. In the case of random oscillations, the "shaping system" is an elastic system described by the common differential equation of the second order: X ?(t)+2hX ?(t)+ ?_0^2 X(t)=E(t), where ?0 = 2?/Т0 is the natural frequency, T0 is the oscillation period, and h is a damping factor. As a result, the process X(t) can be characterized in terms of the system parameters – natural frequency and logarithmic oscillations decrement ? = hT0 as well as the process variance. Evaluation of these parameters is subjected to experimental data processing based on frequency or time-domain representations of oscillations. It must be noted that a concept of these parameters evaluation did not change much during the last century. For instance, in case of the spectral density utilization, evaluation of the decrement values is linked with bandwidth measurements at the points of half-power of the observed oscillations. For a time-domain presentation, evaluation of the decrement requires measuring covariance values delayed by a time interval divisible by T0. Both estimation procedures are derived from a continuous description of research phenomena, so the accuracy of estimates is linked directly to the adequacy of discrete representation of random oscillations. This approach is similar a concept of transforming differential equations to difference ones with derivative approximation by corresponding finite differences. The resulting discrete model, being an approximation, features a methodical error which can be decreased but never eliminated. To render such a presentation more accurate it is imperative to decrease the discretization interval and to increase realization size growing requirements for computing power. The spectral density and covariance function estimates comprise a non-parametric (non-formal) approach. In principle, any non-formal approach is a kind of art i.e. the results depend on the performer’s skills. Due to interference of subjective factors in spectral or covariance estimates of random signals, accuracy of results cannot be properly determined or justified. To avoid the abovementioned difficulties, the application of linear time-series models with well-developed procedures for parameter estimates is more advantageous. A method for the analysis of random oscillations using a parametric model corresponding discretely (no approximation error) with a linear elastic system is developed and presented in this book. As a result, a one-to-one transformation of the model’s numerical factors to logarithmic decrement and natural frequency of random oscillations is established. It allowed to develop a formal processing procedure from experimental data to obtain the estimates of ? and ?0. The proposed approach allows researchers to replace traditional subjective techniques by a formal processing procedure providing efficient estimates with analytically defined statistical uncertainties.
Автор: J. Richard Duro, Lopez Fernando Pena Название: Digital Image and Signal Processing for Measurement Systems ISBN: 8792329292 ISBN-13(EAN): 9788792329295 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an overview of advanced digital image and signal processing techniques that are currently being applied in the realm of measurement systems. The book is a selection of extended versions of the best papers presented at the Sixth IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2011 related to this topic and encompass applications that go from multidimensional imaging to evoked potential detection in brain computer interfaces. The objective was to provide a broad spectrum of measurement applications so that the different techniques and approaches could be presented. Digital Image and Signal Processing for Measurement Systems concentrates on signal processing for measurement systems and its objective is to provide a general overview of the area and an appropriate introduction to the topics considered. This is achieved through 10 chapters devoted to current topics of research addressed by different research groups within this area. These 10 chapters reflect advances corresponding to signals of different dimensionality. They go from mostly one dimensional signals in what would be the most traditional area of signal processing realm to RGB signals and to signals of very high dimensionality such as hyperspectral signals that can go up to dimensionalities of more than one thousand. The chapters have been thought out to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area. They provide an overview of some of the problems in the area of signal and image processing for measurement systems and the approaches and techniques that relevant research groups within this area are employing to try to solve them which, in many instances are the state of the art of some of these topics.
Автор: Frank Scherbaum Название: Basic Concepts in Digital Signal Processing for Seismologists ISBN: 3540579737 ISBN-13(EAN): 9783540579731 Издательство: Springer Рейтинг: Цена: 13060.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Describing how digital signal processing has become an integral part of observational seismology, this monograph describes the basic theory of linear systems, the design and analysis of simple digital filters, the effect of sampling and the spectral analysis of digital signals.
Автор: Jose Maria Giron-Sierra Название: Digital Signal Processing with Matlab Examples, Volume 2 ISBN: 9811025363 ISBN-13(EAN): 9789811025365 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs.This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.
Автор: Pilato George Название: Framework of Digital Signal Processing ISBN: 1632382059 ISBN-13(EAN): 9781632382054 Издательство: Неизвестно Цена: 23335.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering.
Автор: Ingle Vinay Название: Digital Signal Processing Using Matlab ISBN: 1111427380 ISBN-13(EAN): 9781111427382 Издательство: Cengage Learning Рейтинг: Цена: 13779.00 р. Наличие на складе: Нет в наличии.
Описание: The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. There remains a need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. This book attempts to satisfy the above requirement. The algorithms are made clear using MATLAB programs.
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