Signal and Information Processing, Networking and Computers, Songlin Sun; Na Chen; Tao Tian
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.
Описание: This updated edition gives readers hands-on experience in real-time DSP using a practical, step-by-step framework that also incorporates demonstrations, exercises, and problems, coupled with brief overviews of applicable theory and MATLAB applications. Organized in three sections that cover enduring fundamentals and present practical projects and invaluable appendices, this new edition provides support for the most recent and powerful of the inexpensive DSP development boards currently available from Texas Instruments: the OMAP-L138 LCDK. It includes two new real-time DSP projects, as well as three new appendices: an introduction to the Code Generation tools available with MATLAB, a guide on how to turn the LCDK into a portable battery-operated device, and a comparison of the three DSP boards directly supported by this edition.
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.
Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key techniques and comprehend the current research literature, the book offers a comprehensive overview of methods and applications from linear algebra, numerical analysis, statistics, probability, stochastic processes, and optimization.
From basic transforms to Monte Carlo simulation to linear programming, the text covers a broad range of mathematical techniques essential to understanding the concepts and results in signal processing, telecommunications, and networking. Along with discussing mathematical theory, each self-contained chapter presents examples that illustrate the use of various mathematical concepts to solve different applications. Each chapter also includes a set of homework exercises and readings for additional study.
This text helps readers understand fundamental and advanced results as well as recent research trends in the interrelated fields of signal processing, telecommunications, and networking. It provides all the necessary mathematical background to prepare students for more advanced courses and train specialists working in these areas.
Автор: Marzetta Название: Fundamentals of Massive MIMO ISBN: 1107175577 ISBN-13(EAN): 9781107175570 Издательство: Cambridge Academ Рейтинг: Цена: 11405.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by the concept`s pioneers, this is the first complete guide to the physical and engineering principles of Massive MIMO. Richly illustrated by numerous case studies, it covers key topics such as propagation models, channel modeling, and cell analysis, and stresses capacity bounds. Problem sets and solutions are provided online.
Автор: Hayes, Monson H. Название: Statistical digital signal processing and modeling ISBN: 0471594318 ISBN-13(EAN): 9780471594314 Издательство: Wiley Рейтинг: Цена: 45636.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book responds to the dramatic growth in digital signal processing (DSP) over the past decade. While its focal point is signal modeling, the book integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectral estimation, and adaptive filtering.
Автор: De Maio Antonio Название: Compressed Sensing in Radar Signal Processing ISBN: 1108428290 ISBN-13(EAN): 9781108428293 Издательство: Cambridge Academ Рейтинг: Цена: 18216.00 р. Наличие на складе: Поставка под заказ.
Описание: Provides broad and accessible coverage of the latest theoretical and practical advances in radar signal processing using tools from compressive sensing, including clutter rejection, CFAR detection, and adaptive beamforming. It is ideal for researchers, graduate students and industry professionals working in signal processing and radar.
Автор: Andy W.H. Khong, Yong Liang Guan Название: Recent Advances in Information, Communications and Signal Processing ISBN: 8793609434 ISBN-13(EAN): 9788793609433 Издательство: Taylor&Francis Рейтинг: Цена: 13320.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Research in information, communications and signal processing has brought about new services, applications and functions in a large number of fields which include consumer electronics, biomedical devices and defence. These applications play an important role in advancing technologies to enhance human life in general. Recent Advances in Information, Communications and Signal Processing aims to give students, researchers, and engineers information pertaining to recent advances in these fields. In terms of research in signal processing topics, the two chapters included in this book have a strong emphasis on advances in algorithmic development in the biomedical, and human-computer interfaces domain areas. More specifically, the use of deep learning for placental maturity staging is discussed as well as the use of vibration analysis for localising impacts on surfaces for human-computer applications. In terms of communications signal processing, advances in new wireless communication such as NOMA (non-orthogonal multiple access) and millimetre-wave antenna design for 5G cellular mobile radio, as well as innovations in LDPC (low density parity check code) decoding and networking coding, are featured.
Описание: The Signal connects everything to everything else, in both communication, and in the metaphorical sense as the link between and among people.
Описание: This proceedings book presents the latest research in the fields of information theory, communication system, computer science and signal processing, as well as other related technologies.
Описание: This proceedings book presents selected papers from the 4th Conference on Signal and Information Processing, Networking and Computers (ICSINC) held in Qingdao, China on May 23–25, 2018. It focuses on the current research in a wide range of areas related to information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource anyone interested in this field.
Описание: The Signal connects everything to everything else, in both communication, and in the metaphorical sense as the link between and among people.
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