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ELE 391 Random Signals
Spring 2016
Homework 1: (Due 9:30AM on Tuesday Feb 9)
(Only four problems will be graded chosen at random)
Problems from end of Chapter 1
Work Problems 1, 5, 7, 14, 18, 22, 27, 30, 32, 34
/100
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ELE 391 Random Signals
Spring 2016
Homework 2: (Due 9:30AM on Thursday Feb 11)
(Only four problems will be graded chosen at random)
Problems from end of Chapter 2
Work Problems 1, 3, 6, 9, 14, 16, 18, 21
/100
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ELE 391 Random Signals
Spring 2016
Homework 4: (Due 9:30AM on Thursday Feb 25)
(Only four problems will be graded selected at random)
Problems from end of Chapter 3
Solve Problems 10, 12, 13, 14, 16, 18, 22, 25
/100
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ELE 391 Random Signals
Spring 2016
Homework 3: (Due 9:30AM on Thursday Feb 18)
(Only four problems will be graded selected at random)
Problems from end of Chapter 3
Solve Problems 1, 4, 7, 11
/100
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ELE 391 Random Signals
Spring 2016
Homework 2: (Due 9:30AM on Thursday Feb 11)
(Only four problems will be graded chosen at random)
Problems from end of Chapter 2
Problem 1: 96
Problem 3: A- 0.28 B- 0.139
Problem 6: 0.242
Problem 9:
A-
p
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GRADE
ELE 391 Random Signals
Spring 2016
Homework 3: (Due 9:30AM on Thursday Feb 18)
(Only four problems will be graded selected at random)
Problems from end of Chapter 3
Problem 1
a- Rxcfw_0,1,2
b- 1/ 6
c- 1/3
d- 3/ 5
Problem 4
a- 1/ 8
b- 7/ 8
Chapter 1
Bayes Rule
Introduction
What is Probability?
Review of Set
Theory
This rule allows us to calculate P(B|A) from P(A|B).
For two events A and B, we have
Review
Venn Diagrams
Set Operations
Cardinality
Functions
P(B|A)P(A) = P(A B) = P(A|B)P(B).
Di
Chapter 2
Unordered Sampling with Replacement
Finding
Probabilities Using
Counting Methods
This is the most challenging type of sampling.
Lemma: The total number of distinct k samples from
an n-element set such that repetition is allowed and
ordering does
Hypergeometric Distribution
Chapter 3
Basic Concepts
You have a bag that contains b blue marbles and r red
marbles.
Choose k b + r marbles at random without
replacement.
Let X be the number of blue marbles in your sample.
By denition, X min(k, b) and numb
Chapter 2
Finding Probabilities Using Counting Methods
Finding
Probabilities Using
Counting Methods
Counting methods that can be used for discrete sample
spaces with equally likely outcomes.
For such a nite sample space S, the probability of an
event A is
Chapter 4
Functions of Continuous Random Variables
Introduction
Continuous
Random Variables
and their
Distributions
Example: Let X be a Uniform(0, 1) random variable,
and let Y = e X .
Probability
Distribution Function
Range
Expected Value and
Variance
Ex
Chapter 3
Cumulative Distribution Function (CDF)
Basic Concepts
Cumulative distribution function (CDF) of a random
variable is a method to describe the distribution of
random variables.
The advantage of CDF is that it can be dened for any
kind of random v
Syllabus for ELE 391
Spring 2016
EL E 391 Random Signals
Spring 2016
Time/Location:
T Th 09:30 10:45, Anderson Room 235
Instructor:
Dr. Mustafa M. Matalgah
Office: Anderson Hall 12, Phone: 915-5381, Email: [email protected]
Office Hours:
M W F 09:00 - 1
-. \
t _
i \i i," .1.
7H J
Instructor: Dr. R. Viswanathan "' ELE 391 Random Signals Time: 75 minutes
Spring 2013 Exam 3 Closed Book, Closed Notes Maximum POintS 15
r r'f : 5 y L " l '
1. Consider two random variables, X and Y with the joint CDF,
; n
ISU'UCtOIZ Dr. R, Viswanathan ELE 391 Random Signals Time: 75 minutes
Spring 2014 Exam 2 Closed Book, Closed Notes Maximum Points 50
1 . . . . _ _ 0.3 x=1.2
. e a iscrete random variable wrth probability mass function, P(X x) - O 4 x = 0
Find the mean and
PRINT NAME
GRADE
ELE 391 Random Signals
Spring 2016
Homework 1: (Due 9:30AM on Tuesday Feb 9)
(Only four problems will be graded chosen at random)
Problems from end of Chapter 1
Work Problems 1, 5, 7, 14, 18, 22, 27, 30, 32, 34
Problem 1
A- cfw_1, 2, 3, 4