{"id":56,"title":"Digital Signal Processing","credit_hour":"3","lecture_hour":"45","outcome":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ul>\r\n<li>Analyze and implement digital signal processing systems in time domain.<\/li>\r\n<li>Compute the Fourier series and the discrete time Fourier transform (DTFT) of discrete-time signals.<\/li>\r\n<li>Appreciate the importance of the z-transform and the impulse response and transfer function of a digital filter.<\/li>\r\n<li>Have familiarity with ideal filter approximation functions.<\/li>\r\n<li>Design digital filters to meet prescribed specifications.<\/li>\r\n<li>Analyze and implement digital systems using the DFT and the Fast Fourier Transform (FFT).<\/li>\r\n<\/ul>\r\n<\/body>\r\n<\/html>","description":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<p style=\"text-align: justify;\">This senior-level course serves as an introduction to the fundamentals, implementation and applications of DSP. Will be useful for students looking to do graduate courses in communications and signal processing. Topics include: The mathematics of signals and linear systems; Fourier and Laplace transforms, discrete Fourier and Z transforms; Analogue filters: approximation theory, Butterworth, Bessel, Chebyshev and elliptic filters; Filter impulse and frequency responses, stability, and sensitivity; Sampling continuous signals: the sampling theorem, reconstruction, and aliasing; The discrete Fourier transform (DFT) and the fast Fourier transform (FFT); Fundamentals of the design and realization of finite impulse response (FIR) and infinite impulse response (IIR) digital filters; Digital processing of analog signals, including applications of digital signal processing (DSP) and programmable DSP chips; The representation and modelling of non-deterministic (random) signals, correlation functions, and power density spectra.<\/p>\r\n<\/body>\r\n<\/html>","books":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<p><em>Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition)<\/em> by John G. Proakis and Dimitris K Manolakis<\/p>\r\n<\/body>\r\n<\/html>","created_at":"2016-09-03 13:41:28","updated_at":"2016-09-03 13:41:28"} Details | Department of Computer Science and Engineering, IUB

CNC 640: Digital Signal Processing

Offered Under: M.Sc. in Computer Networks & Communications (CNC)

Description

This senior-level course serves as an introduction to the fundamentals, implementation and applications of DSP. Will be useful for students looking to do graduate courses in communications and signal processing. Topics include: The mathematics of signals and linear systems; Fourier and Laplace transforms, discrete Fourier and Z transforms; Analogue filters: approximation theory, Butterworth, Bessel, Chebyshev and elliptic filters; Filter impulse and frequency responses, stability, and sensitivity; Sampling continuous signals: the sampling theorem, reconstruction, and aliasing; The discrete Fourier transform (DFT) and the fast Fourier transform (FFT); Fundamentals of the design and realization of finite impulse response (FIR) and infinite impulse response (IIR) digital filters; Digital processing of analog signals, including applications of digital signal processing (DSP) and programmable DSP chips; The representation and modelling of non-deterministic (random) signals, correlation functions, and power density spectra.

Prerequisites:

None

Course Type	Major
Credit Hour	3
Lecture Hour	45

Expected Outcome(s):

Analyze and implement digital signal processing systems in time domain.
Compute the Fourier series and the discrete time Fourier transform (DTFT) of discrete-time signals.
Appreciate the importance of the z-transform and the impulse response and transfer function of a digital filter.
Have familiarity with ideal filter approximation functions.
Design digital filters to meet prescribed specifications.
Analyze and implement digital systems using the DFT and the Fast Fourier Transform (FFT).

Suggested Books:

Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition) by John G. Proakis and Dimitris K Manolakis

Grading Policy: