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CITATION

Hsu, Hwei. Schaum's Outline of Probability, Random Variables, and Random Processes, 3rd Edition. US: McGraw-Hill, 2014.

Schaum's Outline of Probability, Random Variables, and Random Processes, 3rd Edition

Authors: Hwei Hsu

Published:  March 2014

eISBN: 9780071824774 0071824774 | ISBN: 9780071822985
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  • Cover
  • Video Content
  • Title Page
  • Copyright Page
  • Contents
  • Chapter 1 Probability
  • 1.1 Introduction
  • 1.2 Sample Space and Events
  • 1.3 Algebra of Sets
  • 1.4 Probability Space
  • 1.5 Equally Likely Events
  • 1.6 Conditional Probability
  • 1.7 Total Probability
  • 1.8 Independent Events
  • Solved Problems
  • Chapter 2 Random Variables
  • 2.1 Introduction
  • 2.2 Random Variables
  • 2.3 Distribution Functions
  • 2.4 Discrete Random Variables and Probability Mass Functions
  • 2.5 Continuous Random Variables and Probability Density Functions
  • 2.6 Mean and Variance
  • 2.7 Some Special Distributions
  • 2.8 Conditional Distributions
  • Solved Problems
  • Chapter 3 Multiple Random Variables
  • 3.1 Introduction
  • 3.2 Bivariate Random Variables
  • 3.3 Joint Distribution Functions
  • 3.4 Discrete Random Variables—Joint Probability Mass Functions
  • 3.5 Continuous Random Variables—Joint Probability Density Functions
  • 3.6 Conditional Distributions
  • 3.7 Covariance and Correlation Coefficient
  • 3.8 Conditional Means and Conditional Variances
  • 3.9 N-Variate Random Variables
  • 3.10 Special Distributions
  • Solved Problems
  • Chapter 4 Functions of Random Variables, Expectation, Limit Theorems
  • 4.1 Introduction
  • 4.2 Functions of One Random Variable
  • 4.3 Functions of Two Random Variables
  • 4.4 Functions of n Random Variables
  • 4.5 Expectation
  • 4.6 Probability-Generating Functions
  • 4.7 Moment-Generating Functions
  • 4.8 Characteristic Functions
  • 4.9 The Laws of Large Numbers and the Central Limit Theorem
  • Solved Problems
  • Chapter 5 Random Processes
  • 5.1 Introduction
  • 5.2 Random Processes
  • 5.3 Characterization of Random Processes
  • 5.4 Classification of Random Processes
  • 5.5 Discrete-Parameter Markov Chains
  • 5.6 Poisson Processes
  • 5.7 Wiener Processes
  • 5.8 Martingales
  • Solved Problems
  • Chapter 6 Analysis and Processing of Random Processes
  • 6.1 Introduction
  • 6.2 Continuity, Differentiation, Integration
  • 6.3 Power Spectral Densities
  • 6.4 White Noise
  • 6.5 Response of Linear Systems to Random Inputs
  • 6.6 Fourier Series and Karhunen-Loéve Expansions
  • 6.7 Fourier Transform of Random Processes
  • Solved Problems
  • Chapter 7 Estimation Theory
  • 7.1 Introduction
  • 7.2 Parameter Estimation
  • 7.3 Properties of Point Estimators
  • 7.4 Maximum-Likelihood Estimation
  • 7.5 Bayes’ Estimation
  • 7.6 Mean Square Estimation
  • 7.7 Linear Mean Square Estimation
  • Solved Problems
  • Chapter 8 Decision Theory
  • 8.1 Introduction
  • 8.2 Hypothesis Testing
  • 8.3 Decision Tests
  • Solved Problems
  • Chapter 9 Queueing Theory
  • 9.1 Introduction
  • 9.2 Queueing Systems
  • 9.3 Birth-Death Process
  • 9.4 The M/M/1 Queueing System
  • 9.5 The M/M/s Queueing System
  • 9.6 The M/M/1/K Queueing System
  • 9.7 The M/M/s/K Queueing System
  • Solved Problems
  • Chapter 10 Information Theory
  • 10.1 Introduction
  • 10.2 Measure of Information
  • 10.3 Discrete Memoryless Channels
  • 10.4 Mutual Information
  • 10.5 Channel Capacity
  • 10.6 Continuous Channel
  • 10.7 Additive White Gaussian Noise Channel
  • 10.8 Source Coding
  • 10.9 Entropy Coding
  • Solved Problems
  • Appendix A: Normal Distribution
  • Appendix B: Fourier Transform
  • B.1 Continuous-Time Fourier Transform
  • B.2 Discrete-Time Fourier Transform
  • Index