Lecture1_Spring11

Lecture1_Spring11 - ELEC 210: Probability and Random...

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ELEC 210: Probability and Random Processes in Engineering 1 Spring 2011 Instructor: Prof. Jun ZHANG Office: 2448 Tel: 2358 7050 Email: eejzhang@ust.hk Webpage: http://www.ece.ust.hk/~eejzhang/
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Elec210 Lecture 1 2 Elec 210: Lecture 1 Course Details Models in Engineering Their role Types of models An Interesting Problem – Winning an iPad Relative Frequency Axiomatic Approach to Probability Packet Voice Transmission Example
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Elec210 Lecture 1 3 Course Details Weekly schedule 2 lectures per week (Wed and Fri, 15:00—16:20, Room 3008) Tutorial starts from the 2 nd week (Mon 10:30-11:20, LTD) Grading: Homework (20%) Mid-Term (30%) + Final (50%) Homework assignments Roughly once every 2 weeks (7~8 in total) Details of homework submission procedures and late penalties on website (see next slide)
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Elec210 Lecture 1 4 Course Details Website http://course.ee.ust.hk/elec210/ Textbook: Probability, Statistics and Random Processes for Electrical Engineering , Alberto Leon-Garcia, Addison Wesley, 3 rd ed., 2009.
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Course Details Course Structure Part I: Basic probability theory. (~2-3 weeks) Part II: Single random variables. (~3-4 weeks) Part III: Multiple random variables. (~5 weeks) Part IV: Stochastic processes. (~3 weeks) Objective of the course Basic concepts of probability theory required to understand probability models used in engineering. Basic techniques required to develop probability models. Elec210 Lecture 1
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Elec210 Lecture 1 6 Course Details Teaching Assistants: HUANG Shanshan, sshuang@ust.hk HU Xiuwen, xhu@ust.hk ZHANG Ying, victoria@ust.hk Office location and consultation hours will be posted on website TAs are there to help you – PLEASE USE THEM!
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Elec210 Lecture 1 7 Elec 210: Lecture 1 Course Details Models in Engineering Their role Types of models An Interesting Problem – Winning an iPad Relative Frequency Axiomatic Approach to Probability Packet Voice Transmission Example
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Elec210 Lecture 1 8 Modelling In engineering as well as in daily life, we are faced with choices Our decisions are based on our belief – our model – of how things will behave A model is an approximate representation of a physical situation which attempts to explain observed behavior Good models are simple and understandable predict all relevant aspects of the situation Models can help us avoid costly (in time and money) experimentation
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Elec210 Lecture 1 9 Mathematical and Computer Simulation Models Mathematical model A set of assumptions about how a system or physical process works. Assumptions are stated in the form of mathematical relations between the important parameters and variables. By solving these relations, we can predict the outcome of an experiment, e.g. V = I*R (Ohm’s law) The simpler the model, the easier it is to solve, understand and analyze.
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This note was uploaded on 03/27/2011 for the course ELEC 202 taught by Professor ? during the Spring '11 term at HKUST.

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Lecture1_Spring11 - ELEC 210: Probability and Random...

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