Academics

Graduate Program

Academics

Graduate Program

Graduate Program

Advanced Signal Detection

Subject No.
Research
Credit
Classification
Prerequisite
EE722
Communication
3
72

This course is to discuss some important advanced topics in the area of signal detection theory. Topics may vary: In Fall 2005, the main topic will be locally-optimum detection of weak signals.
(Prerequisite: {EE528 and EE622} or {Approval of the Instructor})

Recommend

Communication
EE621

This course is the advanced course dealing with methods for correcting and detecting errors in data and covers finite field theory, cyclic code, BCH code, Reed-Solomon code, convolutional code, trellis-coded modulation, turbo code, LDPC code, space-time code, and adaptive coding. (Prerequisite: EE522, EE528)

Communication, Signal
EE622

The purpose of this course is to provide the fundamental background behind detection and estimation theories based on likelihood functions as well as on Bayesian principles. Topics to be covered are decision theory, hypothesis testing, performance analysis, detection and estimation from waveform observation, linear and nonlinear parameter estimations. (Prerequisite: EE528 recommended)

Communication, Signal
EE623

This course covers the core concept of information theory, including the fundamental source and channel coding theorems, coding theorem for Gaussian channel, rate-distortion theorem, vector quantization, multiple user channel, and multiple access channels.
(Prerequisite: CC511, EE528)

 

This course aims to learn fundamental technologies for signal modeling and estimation and covers deterministic and random signal modeling, lattice filter realization, parameter, and signal estimation, Wiener and Kalman filter design, parametric and nonparametric spectrum estimation, and adaptive filtering. (Prerequisite: EE432, EE528)