Probability and Random Processes for Electrical Engineering, Leon-Garc…
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4.1 The Cumulative Distribution Function 141
C. Matrices and Linear Algebra
Problems 402
CHAPTER 11 Markov Chains 647
CHAPTER 6 Vector Random Variables 303
7.2 The Sample Mean and the Laws of Large Numbers 365
9.4 Poisson and Associated Random Processes 507
4.4 Important Continuous Random Variables 163
10.5 The Kalman Filter 617
9.7 Continuity, Derivatives, and Integrals of Random Processes 529
CHAPTER 4 One Random Variable 141
Weak Law of Large Numbers 367
다.
7.4 Convergence of Sequences of Random Variables 378
Problems 635
12.8 Burke’s Theorem: Departures From M/M/c Systems 754
Summary 129
2.3 Computing Probabilities Using Counting Methods 41
3.1 The Notion of a Random Variable 96
8.2 Parameter Estimation 415
3.6 Generation of Discrete Random Variables 127
CHAPTER 7 Sums of Random Variables and Long-Term Averages 359
4.3 The Expected Value of X 155
Probability and Random Processes for Electrical Engineering, Leon-Garcia, solution 이에 대한 솔루션입니다. 밑에는 목차를 올렸습니다. 10.2 Response of Linear Systems to Random Signals 587
Summary 782
1.6 Overview of Book 16
4.9 Computer Methods for Generating Random Variables 194
7.6 Calculating Distribution’s Using the Discrete Fourier
CHAPTER 2 Basic Concepts of Probability Theory 21
Summary 286
10.6 Estimating the Power Spectral Density 622
1.3 Probability Models 4
Central Limit Theorem 370
8.4 Confidence Intervals 430
10.4 Optimum Linear Systems 605
8.6 Bayesian Decision Methods 455
11.3 Classes of States, Recurrence Properties, and Limiting
11.6 Numerical Techniques for Markov Chains 692
6.4 Jointly Gaussian Random Vectors 325
B. Tables of Fourier Transforms 800
5.8 Functions of Two Random Variables 271
12.4 Multi-Server Systems: M/M/c, M/M/c/c,And 727
Summary 400
12.1 The Elements of a Queueing System 714
8.3 Maximum Likelihood Estimation 419
10.3 Bandlimited Random Processes 597
11.1 Markov Processes 647
CHAPTER 12 Introduction to Queueing Theory 713
Problems 471
5.3 The Joint cdf of X and Y 242
CHAPTER 9 Random Processes 487
8.7 Testing the Fit of a Distribution to Data 462
Variables 257
and Brownian Motion 514
Probabilities 660
9.1 Definition of a Random Process 488
확률, 통계
9.5 Gaussian Random Processes,Wiener Process
Problems 702
12.2 Little’s Formula 715
5.10 Generating Independent Gaussian Random Variables 284
9.3 Discrete-Time Processes: Sum Process, Binomial Counting Process,
1.4 A Detailed Example: A Packet Voice Transmission System 9
11.5 Time-Reversed Markov Chains 686
Summary 213
and Computer Engineering 1
5.6 Joint Moments and Expected Values of a Function of Two Random
CHAPTER 5 Pairs of Random Variables 233
2.7 Synthesizing Randomness: Random Number Generators 67
5.5 Independence of Two Random Variables 254
4.2 The Probability Density Function 148
Problems 348
설명
5.4 The Joint pdf of Two Continuous Random Variables 248
CHAPTER 1 Probability Models in Electrical
5.2 Pairs of Discrete Random Variables 236
9.6 Stationary Random Processes 518
5.1 Two Random Variables 233
A. Mathematical Tables 797
Summary 633
12.10 Simulation and Data Analysis of Queueing Systems 771
7.5 Long-Term Arrival Rates and Associated Averages 387
8.1 Samples and Sampling Distributions 411
6.6 Generating Correlated Vector Random Variables 342
9.2 Specifying a Random Process 491
이에 대한 해법입니다.
6.3 Expected Values of Vector Random Variables 318
4.5 Functions of a Random Variable 174
Problems 130
순서
3.3 Expected Value and Moments of Discrete Random Variable 104
4.7 Transform Methods 184
7.1 Sums of Random Variables 360
Strong Law of Large Numbers 368
2.6 Sequential Experiments 59
2.5 Independence of Events 53
9.8 Time Averages of Random Processes and Ergodic Theorems 540
Appendices
4.10 Entropy 202
12.6 M/G/1 Queueing Systems 738
Summary 469
and Random Walk 498
2.1 Specifying Random Experiments 21
10.1 Power Spectral Density 577
4.6 The Markov and Chebyshev Inequalities 181
2.8 Fine Points: Event Classes 70
Summary 79
Summary 17
2.9 Fine Points: Probabilities of Sequences of Events 75
9.10 Generating Random Processes 550
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8.5 Hypothesis Testing 441
3.5 Important Discrete Random Variables 115
3.2 Discrete Random Variables and Probability Mass Function 99
Summary 554
1.2 Deterministic Models 4
Summary 346
6.2 Functions of Several Random Variables 309
Probability and Random Processes for Electrical Engineering, Leon-Garcia, solution
6.1 Vector Random Variables 303
1.5 Other Examples 11
11.4 Continuous-Time Markov Chains 673
Problems 784
Problems 557
7.3 The Central Limit Theorem 369
12.3 The M/M/1 Queue 718
2.2 The Axioms of Probability 30
Problems 288
Transform 392
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12.7 M/G/1 Analysis Using Embedded Markov Chains 745
5.9 Pairs of Jointly Gaussian Random Variables 278
Problems 215
9.9 Fourier Series and Karhunen-Loeve Expansion 544
4.8 Basic Reliability Calculations 189
Problems 18
Probability and Random Processes for Electrical Engineering, Leon-Garcia, solution 랜덤프로세스 해법
레포트 > 공학,기술계열
11.2 Discrete-Time Markov Chains 650
10.7 Numerical Techniques for Processing Random Signals 628
3.4 Conditional Probability Mass Function 111
Summary 700
6.5 Estimation of Random Variables 332
CHAPTER 8 Statistics 411
CHAPTER 3 Discrete Random Variables 96
12.5 Finite-Source Queueing Systems 734
1.1 Mathematical Models as Tools in Analysis and Design 2
CHAPTER 10 Analysis and Processing of Random Signals 577
5.7 Conditional Probability and Conditional Expectation 261
2.4 Conditional Probability 47
Problems 80
12.9 Networks of Queues: Jackson’s Theorem 758
밑에는 목차를 올렸습니다.
