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Course number and title: EE241A Stochastic Processes
Credits: 4
Instructor(s)-in-charge: S. Diggavi (suhas@ee.ucla.edu)
Course type: Lecture
Required or Elective: A Signals and Systems course
Course Schedule:
Lecture: 4 hrs/week
Outside Study: 8 hrs/week
Office Hours: 2 hrs/week
 
Course Assessment:
Homework: 5 assignments
Exams: 1 midterm and 1 final
 
Grading Policy: Typically, 10% HW, 40% Midterm, 50% Final.
Course Prerequisites: EE131B
Catalog Description: Random process models: basic concepts, properties. Stationary random processes: covariance and spectrum. Response of linear systems to random inputs: discrete-time and continuous-time models. Time averages and ergodic principle. Sampling principle and interpolation. Simulation of random processes.  
Textbook and any related course material:
A.V. Balakrishnan, Introduction to Random Processes in Engineering, Wiley, NY, 1995.
 
Course Website
Topics covered in the course:
Random Process Models: Basic Concepts, Properties.
Stationary Random Processes: Gaussian Processes, Covariance and Spectrum.
Response of Linear Systems to Random Inputs: Discrete-time Models.
Response of Linear Systems to Random Inputs: Continuous-time Models.
Time Averages and the Ergodic Principle.
Sampling Principle and Interpolation.
Simulation of Random Processes.
Will this course involve computer assignments? NO Will this course have TA(s) when it is offered? NO

:: Last modified: September 2011 by C. Chiuco ::

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