隨機過程 Stochastic Processes
課程目標/概述
The course aims to provide the fundamentals of discrete time signal processing.
課程章節
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單元主題
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Chapter 9: General Concepts
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9-1 Definitions
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9-2 Systems with Stochastic Inputs
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9-3 The Power Spectrum
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9-4 Discrete-Time Processes
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Chapter 10: Random Walks and Other Applications
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10-3 Modulation
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10-4 Cyclostationary Processes
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10-5 Bandlimited Processes and Sampling Theory
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10-6 Deterministic Signals in Noise
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Appendix 10A The Poisson Sum Formula
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Chapter 11: Spectral Representation
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11-1 Factorization and Innovations
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11-2 Finite-Order Systems and State Variables
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11-3 Fourier Series and Karhunen-Lo´eve Expansions
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11-4 Spectral Representation of Random Processes
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Chapter 12: Spectrum Estimation
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12-1 Ergodicity
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12-2 Spectrum Estimation
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Chapter 13: Mean Square Estimation
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13-1 Introduction
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13-2 Prediction (Partially, 12-3 Lattice Filters and Levinson’s
Algorithm)
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課程書目
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Athanasios Papoulis & S. Unnikrishna Pillai, Probability, Random Variables
and Stochastic Processes. Fourth edition, Mc Graw Hill, 2002.
評分標準
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項目 |
百分比 |
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three quizzes |
25% |
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two midterm exam |
50% |
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final exam |
25% |
