Electrical Engineering 431 Problem Set V Due: March 12, 2004
5.1 Laplacian Random Variables A random variable is said to be Laplacian if its probability density function has the form
and are positive constants. and so that
Electrical Engineering 431 Problem Set VIII Due: April 9, 2004
8.1 Image Restoration Nuclear medicine imaging systems can be modeled as a blurring process (lowpass filtering) plus additive noise.
the unit-sample response of the blurring
Electrical Engineering 431 Problem Set III Due: February 6, 2004
Reading: OSB: 5.15.6 3.1 Properties of Allpass Filters . This signal Let be a causal signal that equals zero outside the domain serves as the input to a system having an input-out
Electrical Engineering 430 Problem Set I Due: January 23, 2004
Reading: OSB: 2.1-2.9 1.1 Approximating Continuous-Time Filters We want to approximate the continuous-time operation of differentiation with a discrete-time counterpart. (a) Show that dif
ELEC 431: Digital Signal Processing
ELEC 431: Digital Signal Processing Course Overview
Class meets MWF at 11AM in Duncan Hall 1046. Instructor Office Hours: Thursdays 1:30-3:30, Abercrombie A204.
The course covers deterministic and stochastic d
Electrical Engineering 431 Problem Set IV Due: February 23, 2004
Reading: OSB: Chapter 7 4.1 Filter Design Your boss wants you to design a digital filter according to the following specifications.
(a) Design a Chebyshev fi
Electrical Engineering 431 Problem Set VI Due: March 19, 2004
Reading: OSB: Appendix A 6.1 A Simple Random Process is defined by the following equally likely sample functions.
(a) (b) 6.2
Determine the mean and correlation funct
Electrical Engineering 431 Problem Set VII Due: March 26, 2004
7.1 Other Optimal Filters The Eckhart filter is an optimal linear filter that maximizes the signal-to-noise ratio of its output. The filter's output is an estimate of the signal. To find