Class Restriction And Registration Summary

 

EE 60573 - Section 01: Random Processes, Detctn,& Est (CRN 22062)


Course Description:
Fundamentals of random processes, including characterization, convergence issues, covariance and power spectral density. Spectral representations of stochastic processes using Karhunen-Loeve, Fourier, and sampling expansions. Detection and estimation from continueous waveform observations. Other topics: linear prediction and filtering adaptive; Wiener and Kalman filters.

Associated Term: Spring Semester 2013
Campus: Main
Credits: 3
Grade Mode: Standard Letter
Course may not be repeated


Prerequisites:
EE 60563



Restrictions:
Must be enrolled in one of the following Levels:
Employee Non-Degree (EM) ,  Graduate Non-Degree (GD) ,  Graduate (GR)
Must be enrolled in one of the following Campuses:
Main (M)

Course Attributes:
ZTST - Final exam

Registration Availability (Overflow: Off )
  Maximum Actual Remaining
TOTAL 19 8 11


Enhanced Class Search
Instructor's Description of Course » Laneman, J. Nicholas » EE  60573 - Section 01:  Random Processes, Detctn,& Est (CRN 22062)
No descriptions have yet been provided for this course and instructor.
Enrollment History » EE 60573 Random Processes, Detctn,& Est (CRN 22062)
Enrollment over the last three years
Course was recently taught in SP10, SP11, SP12
Average number of students: 11
Composition of Students First Year Soph Junior Senior/5th Grad/Prof
FYS          
Architecture          
Arts and Letters          
Business          
Engineering         100%
Science          
Law          

Was this information helpful?