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Field Guide to Probability, Random Processes, and Random Data Analysis [Spiraalköide]

  • Formaat: Spiral bound, 108 pages, kaal: 141 g
  • Sari: Field Guides
  • Ilmumisaeg: 30-Mar-2012
  • Kirjastus: SPIE Press
  • ISBN-10: 0819487015
  • ISBN-13: 9780819487018
Teised raamatud teemal:
  • Formaat: Spiral bound, 108 pages, kaal: 141 g
  • Sari: Field Guides
  • Ilmumisaeg: 30-Mar-2012
  • Kirjastus: SPIE Press
  • ISBN-10: 0819487015
  • ISBN-13: 9780819487018
Teised raamatud teemal:
Mathematical theory developed in basic courses in engineering and science usually involves deterministic phenomena, and such is the case in solving a differential equation that describes some linear system where both the input and output are deterministic quantities. In practice, however, the input to a linear system, like an imaging system or radar system, may contain a ""random"" quantity that yields uncertainty about the output. Such systems must be treated by probabilistic methods rather than deterministic methods. For this reason, probability theory and random process theory have become indispensable tools in the mathematical analysis of these kinds of engineering systems. Topics included in this Field Guide are basic probability theory, random processes, random fields, and random data analysis.
Sums of N Complex Random Variables
38(10)
Central Limit Theorem
39(1)
Example: Central Limit Theorem
40(1)
Phases Uniformly Distributed on (-π,π)
41(1)
Phases Not Uniformly Distributed on (-π,π)
42(1)
Example: Phases Uniformly Distributed on (-α, α)
43(2)
Central Limit Theorem Does Not Apply
45(1)
Example: Non-Gaussian Limit
46(2)
Random Processes
48(17)
Random Processes Terminology
49(1)
First- and Second-Order Statistics
50(1)
Stationary Random Processes
51(1)
Autocorrelation and Autocovariance Functions
52(1)
Wide-Sense Stationary Process
53(1)
Example: Correlation and PDF
54(1)
Time Averages and Ergodicity
55(1)
Structure Functions
56(1)
Cross-Correlation and Cross-Covariance Functions
57(1)
Power Spectral Density
58(1)
Example: PSD
59(1)
PSD Estimation
60(1)
Bivariate Gaussian Processes
61(1)
Multivariate Gaussian Processes
62(1)
Examples of Covariance Function and PSD
63(1)
Interpretations of Statistical Averages
64(1)
Random Fields
65(7)
Random Fields Terminology
66(1)
Mean and Spatial Covariance Functions
67(1)
1D and 3D Spatial Power Spectrums
68(1)
2D Spatial Power Spectrum
69(1)
Structure Functions
70(1)
Example: PSD
71(1)
Transformations of Random Processes
72(7)
Memoryless Nonlinear Transformations
73(1)
Linear Systems
74(1)
Expected Values of a Linear System
75(1)
Example: White Noise
76(1)
Detection Devices
77(1)
Zero-Crossing Problem
78(1)
Random Data Analysis
79(6)
Tests for Stationarity, Periodicity, and Normality
80(1)
Nonstationary Data Analysis for Mean
81(1)
Analysis for Single Time Record
82(1)
Runs Test for Stationarity
83(2)
Equation Summary 85(5)
Bibliography 90(1)
Index 91