Probabilistic systems and random signals

Author: Abraham H. Haddad
Publisher: Prentice Hall
ISBN:
Format: PDF, Kindle
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In-depth mathematical treatment, including examples of real systems to explain many of the probabilistic models and the use of Matlab both in examples and problem assignments, ensures students can relate to the mathematical material in practical terms Unique applications--covering issues such as reliability, measurement errors, and arrival and departure of events in networks--provide students with a broader range of topical coverage.

Probability Random Signals and Statistics

Author: X. Rong Li
Publisher: CRC Press
ISBN: 9780849304330
Format: PDF, ePub, Docs
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With this innovative text, the study-and teaching- of probability and random signals becomes simpler, more streamlined, and more effective. Its unique "textgraph" format makes it both student-friendly and instructor-friendly. Pages with a larger typeface form a concise text for basic topics and make ideal transparencies; pages with smaller type provide more detailed explanations and more advanced material.

Probabilistic Methods of Signal and System Analysis

Author: George R. Cooper
Publisher: Oxford University Press, USA
ISBN: 9780195123548
Format: PDF, ePub, Mobi
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This text provides an introduction to the applications of probability theory to the solution of problems arising in the analysis of signals and systems. Since its original publication in 1971, this text has been a standard for signals and systems courses that emphasise probability. The new edition incorporates a much greater use of the computer in examples and problems. It increases the number and variety of examples, such as estimating the parameters of random processes and processing them through linear systems. In this edition, the use of the computer is introduced both in text examples and in selected problems. The computer examples are carried out using MATLAB. A number of new sections have been added relating to Benoulli trials, correlation of data sets, smoothing of data, computer computation of correlation functions, and spectral densities and system simulation. Key Features:* Stresses engineering applications of probability theory* Presents the material at a level and in a manner appropriate for engineering majors, as opposed to mathematics majorsSupplement:Solutions Manual: 0195123557Contents:PrefaceIntroduction to ProbabilityRandom VariablesSeveral Random VariablesElements of StatisticsRandom ProcessesCorrelation FunctionsSpectral DensityRepines of Linear Systems to Random InputsOptimum Linear SystemsAppendices: Mathematical TablesFrequently Encountered Probability DistributionsBinomial CoefficientsNormal Probability Distribution FunctionThe Q-FunctionStudent's T-Distribution FunctionComputer ComputationsTable of Correlation Function-Spectral Density PairsContour Integration

Random Signals

Author: K. Sam Shanmugan
Publisher: Wiley
ISBN: 9780471815556
Format: PDF, Kindle
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Random Signals, Noise and Filtering develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: (1) fundamentals and examples of random process models, (2) applications of probabilistic models: signal detection, and filtering, and (3) statistical estimation--measurement and analysis of random data to determine the structure and parameter values of probabilistic models. This volume by Breipohl and Shanmugan offers the only one-volume treatment of the fundamentals of random process models, their applications, and data analysis.

Probability Random Processes and Statistical Analysis

Author: Hisashi Kobayashi
Publisher: Cambridge University Press
ISBN: 1139502611
Format: PDF, ePub, Docs
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Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.

Probabilistic Models for Dynamical Systems Second Edition

Author: Haym Benaroya
Publisher: CRC Press
ISBN: 1439850151
Format: PDF, ePub
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Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing equations. Introduces probabilistic modeling and explores applications in a wide range of engineering fields Identifies and draws on specialized texts and papers published in the literature Develops the theoretical underpinnings and covers approximation methods and numerical methods Presents material relevant to students in various engineering disciplines as well as professionals in the field This book provides a suitable resource for self-study and can be used as an all-inclusive introduction to probability for engineering. It presents basic concepts, presents history and insight, and highlights applied probability in a practical manner. With updated information, this edition includes new sections, problems, applications, and examples. Biographical summaries spotlight relevant historical figures, providing life sketches, their contributions, relevant quotes, and what makes them noteworthy. A new chapter on control and mechatronics, and over 300 illustrations rounds out the coverage.

Probability Statistics and Random Signals

Author: Charles G. Boncelet
Publisher: Oxford University Press, USA
ISBN: 9780190200510
Format: PDF, Docs
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Probability, Statistics, and Random Signals offers a comprehensive treatment of probability, giving equal treatment to discrete and continuous probability. The topic of statistics is presented as the application of probability to data analysis, not as a cookbook of statistical recipes. This student-friendly text features accessible descriptions and highly engaging exercises on topics like gambling, the birthday paradox, and financial decision-making.

Probability and Random Processes

Author: Venkatarama Krishnan
Publisher: John Wiley & Sons
ISBN: 0471998281
Format: PDF, ePub, Docs
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A resource for probability AND random processes, with hundreds of worked examples and probability and Fourier transform tables This survival guide in probability and random processes eliminates the need to pore through several resources to find a certain formula or table. It offers a compendium of most distribution functions used by communication engineers, queuing theory specialists, signal processing engineers, biomedical engineers, physicists, and students. Key topics covered include: * Random variables and most of their frequently used discrete and continuous probability distribution functions * Moments, transformations, and convergences of random variables * Characteristic, generating, and moment-generating functions * Computer generation of random variates * Estimation theory and the associated orthogonality principle * Linear vector spaces and matrix theory with vector and matrix differentiation concepts * Vector random variables * Random processes and stationarity concepts * Extensive classification of random processes * Random processes through linear systems and the associated Wiener and Kalman filters * Application of probability in single photon emission tomography (SPECT) More than 400 figures drawn to scale assist readers in understanding and applying theory. Many of these figures accompany the more than 300 examples given to help readers visualize how to solve the problem at hand. In many instances, worked examples are solved with more than one approach to illustrate how different probability methodologies can work for the same problem. Several probability tables with accuracy up to nine decimal places are provided in the appendices for quick reference. A special feature is the graphical presentation of the commonly occurring Fourier transforms, where both time and frequency functions are drawn to scale. This book is of particular value to undergraduate and graduate students in electrical, computer, and civil engineering, as well as students in physics and applied mathematics. Engineers, computer scientists, biostatisticians, and researchers in communications will also benefit from having a single resource to address most issues in probability and random processes.