## Probabilistic systems and random signals

**Author**: Abraham H. Haddad

**Publisher:**Prentice Hall

**ISBN:**N.A

**Category:**Business & Economics

**Page:**430

**View:**1694

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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.

## Probabilistic Methods of Signal and System Analysis

**Author**: George R. Cooper,Clare D. McGillem

**Publisher:**Oxford University Press, USA

**ISBN:**9780195123548

**Category:**Computers

**Page:**480

**View:**8449

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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

## Probability, Random Signals, and Statistics

**Author**: X. Rong Li

**Publisher:**CRC Press

**ISBN:**9780849304330

**Category:**Technology & Engineering

**Page:**472

**View:**9376

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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.

## Probability, Random Variables, and Random Signal Principles

**Author**: Peyton Z. Peebles,Bertram Emil Shi

**Publisher:**N.A

**ISBN:**9781259007644

**Category:**

**Page:**536

**View:**5727

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## Probability, Random Processes, and Statistical Analysis

*Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance*

**Author**: Hisashi Kobayashi,Brian L. Mark,William Turin

**Publisher:**Cambridge University Press

**ISBN:**1139502611

**Category:**Technology & Engineering

**Page:**N.A

**View:**3533

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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.

## Random Signals

*Detection, Estimation and Data Analysis*

**Author**: K. Sam Shanmugan,Arthur M. Breipohl

**Publisher:**Wiley

**ISBN:**9780471815556

**Category:**Science

**Page:**688

**View:**7075

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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, Statistics, and Random Signals

**Author**: Charles G. Boncelet

**Publisher:**Oxford University Press, USA

**ISBN:**9780190200510

**Category:**Electrical engineering

**Page:**432

**View:**2431

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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

**Category:**Mathematics

**Page:**420

**View:**7178

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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.

## Random Signals and Processes Primer with MATLAB

**Author**: Gordana Jovanovic Dolecek

**Publisher:**Springer Science & Business Media

**ISBN:**1461423864

**Category:**Technology & Engineering

**Page:**530

**View:**3391

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This book provides anyone needing a primer on random signals and processes with a highly accessible introduction to these topics. It assumes a minimal amount of mathematical background and focuses on concepts, related terms and interesting applications to a variety of fields. All of this is motivated by numerous examples implemented with MATLAB, as well as a variety of exercises at the end of each chapter.

## Introduction to Digital Communications

**Author**: Ali Grami

**Publisher:**Academic Press

**ISBN:**0124076580

**Category:**Technology & Engineering

**Page:**604

**View:**6466

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Introduction to Digital Communications explores the basic principles in the analysis and design of digital communication systems, including design objectives, constraints and trade-offs. After portraying the big picture and laying the background material, this book lucidly progresses to a comprehensive and detailed discussion of all critical elements and key functions in digital communications. The first undergraduate-level textbook exclusively on digital communications, with a complete coverage of source and channel coding, modulation, and synchronization. Discusses major aspects of communication networks and multiuser communications Provides insightful descriptions and intuitive explanations of all complex concepts Focuses on practical applications and illustrative examples. A companion Web site includes solutions to end-of-chapter problems and computer exercises, lecture slides, and figures and tables from the text

## Probability Distributions Involving Gaussian Random Variables

*A Handbook for Engineers and Scientists*

**Author**: Marvin K. Simon

**Publisher:**Springer Science & Business Media

**ISBN:**9780387476940

**Category:**Mathematics

**Page:**200

**View:**983

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This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.

## Probabilistic Models for Dynamical Systems, Second Edition

**Author**: Haym Benaroya,Seon Mi Han,Mark Nagurka

**Publisher:**CRC Press

**ISBN:**1439850151

**Category:**Science

**Page:**764

**View:**4198

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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 and Random Processes for Electrical and Computer Engineers

**Author**: John A. Gubner

**Publisher:**Cambridge University Press

**ISBN:**1139457179

**Category:**Technology & Engineering

**Page:**639

**View:**309

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The theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five chapters cover the basics of probability and both discrete and continuous random variables. The later chapters have a more specialized coverage, including random vectors, Gaussian random vectors, random processes, Markov Chains, and convergence. Describing tools and results that are used extensively in the field, this is more than a textbook; it is also a reference for researchers working in communications, signal processing, and computer network traffic analysis. With over 300 worked examples, some 800 homework problems, and sections for exam preparation, this is an essential companion for advanced undergraduate and graduate students. Further resources for this title, including solutions (for Instructors only), are available online at www.cambridge.org/9780521864701.

## High-Dimensional Probability

*An Introduction with Applications in Data Science*

**Author**: Roman Vershynin

**Publisher:**Cambridge University Press

**ISBN:**1108415199

**Category:**Business & Economics

**Page:**296

**View:**5295

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An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

## Random Signals and Noise

*A Mathematical Introduction*

**Author**: Shlomo Engelberg

**Publisher:**CRC Press

**ISBN:**9780849375545

**Category:**Technology & Engineering

**Page:**216

**View:**9105

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Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory. A Firm Foundation Before launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and includes an appendix on the relevant aspects of linear algebra. He offers a careful treatment of Lagrange multipliers and the Fourier transform, as well as the basics of stochastic processes, estimation, matched filtering, the Wiener-Khinchin theorem and its applications, the Schottky and Nyquist formulas, and physical sources of noise. Practical Tools for Modern Problems Along with these traditional topics, the book includes a chapter devoted to spread spectrum techniques. It also demonstrates the use of MATLAB® for solving complicated problems in a short amount of time while still building a sound knowledge of the underlying principles. A self-contained primer for solving real problems, Random Signals and Noise presents a complete set of tools and offers guidance on their effective application.

## Signals, Systems and Inference

**Author**: Alan V. Oppenheim,George C. Verghese

**Publisher:**Prentice Hall

**ISBN:**9780133943283

**Category:**Technology & Engineering

**Page:**608

**View:**8984

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For upper-level undergraduate courses in deterministic and stochastic signals and system engineering An Integrative Approach to Signals, Systems and Inference Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability. Directed primarily to upper-level undergraduates and beginning graduate students in engineering and applied science branches, this new textbook pioneers a novel course of study. Instead of the usual leap from broad introductory subjects to highly specialized advanced subjects, this engaging and inclusive text creates a study track for a transitional course. Properties and representations of deterministic signals and systems are reviewed and elaborated on, including group delay and the structure and behavior of state-space models. The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering for signal detection. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection. The text explores ideas, methods and tools common to numerous fields involving signals, systems and inference: signal processing, control, communication, time-series analysis, financial engineering, biomedicine, and many others. Signals, Systems, and Inference is a long-awaited and flexible text that can be used for a rigorous course in a broad range of engineering and applied science curricula.

## An Introduction to Statistical Signal Processing

**Author**: Robert M. Gray,Lee D. Davisson

**Publisher:**Cambridge University Press

**ISBN:**9781139456289

**Category:**Technology & Engineering

**Page:**N.A

**View:**2890

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This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.

## Introduction to Probability

**Author**: Dimitri P. Bertsekas,John N. Tsitsiklis

**Publisher:**N.A

**ISBN:**9781886529236

**Category:**Mathematics

**Page:**528

**View:**8907

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## Probabilistic models in engineering sciences

**Author**: Harold J. Larson,Bruno O. Shubert

**Publisher:**N.A

**ISBN:**9780471051794

**Category:**Mathematics

**Page:**737

**View:**6470

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