一、課程說明(Course Desc<x>ription)
<br>This course will cover the fundamental theory of random processes with emphasis on 
<br>applications to signal processing and communications. This is a basic yet important 
<br>course for students pursuing studies in these fields. The course will include basic 
<br>concepts on random processes, stationarity, convergence of random sequences, law of 
<br>large numbers, and examples of important random processes such as Poisson processes, 
<br>Gaussian processes, and Markov chains/processes. With applications to communications 
<br>and signal processing, we will also cover topics related to linear systems, spectral 
<br>analysis, estimation, Karhunen-Loeve expansion etc.
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<br>二、指定用書(Text Books)
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<br>Robert G. Gallager, Stochastic Processes: Theory for Applications, Cambridge 
<br>University Press, 2017.
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<br>三、參考書籍(References)
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<br>Athanasios Papoulis and S. Unnikrishna Pillai, "Probability, Random 
<br>Variables, and Stochastic Processes," McGraw Hill, 2002.
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<br>四、教學方式(Teaching Method)
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<br>3+ hours of weekly lectures plus reading assignments and homework.
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<br>五、教學進度(Syllabus)
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<br>1. Brief Review of Probability and Random Variables
<br>2. Random Vectors, Random Sequences, and Random (Stochastic) Processes
<br>3. Poisson Processes
<br>4. Gaussian Random Vectors and Processes
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<br>Midterm
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<br>5. Random Processes in Communications
<br>6. Finite-State and Countable State Markov Chains
<br>7. Markov Processes
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<br>Final Exam
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<br>六、成績考核(Evaluation)
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<br>30% Homework
<br>35% Midterm
<br>35% Final Exam.
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<br> 七、可連結之網頁位址
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<br>https://eeclass.nthu.edu.tw/ 
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