![]() ![]() The text layout is particularly good, with lots of white space and logical use of headers which make it easy to locate a particular topic within a chapter. The material is presented clearly, and solved problems are included in the text. Each chapter is broken down into small subunits, making this a useful reference book as well as a textbook. This book presents a straightforward exposition of the basics of probability and statistics, starting with basic definitions of sample space and events, and proceeding through fairly advanced topics not always included in a one-semester statistics course. Oliver Ibe's Fundamentals of Applied Probability and Random Processes is informed by his experiences teaching the introductory probability and statistics course to junior and senior engineering students at the University of Massachusetts-Lowell, where he is a professor in the Department of Electrical and Computer Engineering. If it were easy to strike a balance between theoretical rigor and practical application, after all, the perfect text would already have been written. Definitions of Some Common Continuous Time SignalsĪPPENDIX F.There are many introductory textbooks on probability and statistics, for two reasons: first, there is a huge market for such books because many university courses require students to take one or more semesters of statistics second, it is difficult to present this material well. ![]() Random Processes in Linear Systemsġ1.7 Bandlimited and Narrowband Random Processesġ1.9 Engineering Application: An Analog Communication Systemġ2.1 Computer Generation of Random Variablesġ2.4 Engineering Application: Simulation of a Coded Digital Communication SystemĪPPENDIX C. Operations on a Single Random VariableĤ.2 Expected Values of Functions of Random VariablesĤ.11 Engineering Application-Scalar QuantizationĤ.12 Engineering Application-Entropy and Source Codingĥ.1 Joint Cumulative Distribution Functionsĥ.4 Conditional Distribution, Density, and Mass Functionsĥ.5 Expected Values Involving Pairs of Random Variablesĥ.8 Joint Characteristic and Related Functionsĥ.9 Transformations of Pairs of Random Variablesĥ.11 Engineering Application: Mutual Information, Channel Capacity, and Channel CodingĦ.1 Joint and Conditional PMFs, CDFs, and PDFsĦ.2 Expectations Involving Multiple Random VariablesĦ.3 Gaussian Random Variables in Multiple DimensionsĦ.4 Transformations Involving Multiple Random VariablesĦ.6 Engineering Application: Linear Prediction of Speechħ.1 Independent and Identically Distributed Random Variablesħ.2 Convergence Modes of Random Sequencesħ.7 Engineering Application: A Radar SystemĨ.1 Definition and Classification of ProcessesĨ.2 Mathematical Tools for Studying Random ProcessesĨ.3 Stationary and Ergodic Random ProcessesĨ.4 Properties of the Autocorrelation FunctionĨ.7 Engineering Application-Shot Noise in a p–n Junction Diodeĩ.1 Definition and Examples of Markov Processesĩ.2 Calculating Transition and State Probabilities in Markov Chainsĩ.5 Engineering Application: A Computer Communication Networkĩ.6 Engineering Application: A Telephone Exchangeġ0.2 The Wiener–Khintchine–Einstein Theoremġ0.6 Engineering Application: PSDs of Digital Modulation FormatsĬHAPTER 11. Random Variables, Distributions, and Density Functionsģ.5 Conditional Distribution and Density Functionsģ.6 Engineering Application: Reliability and Failure RatesĬHAPTER 4. Introduction to Probability TheoryĢ.1 Experiments, Sample Spaces, and EventsĢ.9 Engineering Application-An Optical Communication SystemĬHAPTER 3. This book is intended for practicing engineers and students in graduate-level courses in the topic. There are also discussions on pairs of random variables multiple random variables random sequences and series random processes in linear systems Markov processes and power spectral density. ![]() It introduces the reader to the basics of probability theory and explores topics ranging from random variables, distributions and density functions to operations on a single random variable. The new edition contains more real world signal processing and communications applications. The authors connect the applications discussed in class to the textbook. Exceptional exposition and numerous worked out problems make this book extremely readable and accessible. It also describes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and others. The book includes unique chapters on narrowband random processes and simulation techniques. Probability and Random Processes, Second Edition presents pertinent applications to signal processing and communications, two areas of key interest to students and professionals in today's booming communications industry.
0 Comments
Leave a Reply. |