Digital Signal Processing Fundamentals with Hands-On Experiments (3 days)

Code:  CRS-DSP

Includes Lecture and Hands-On Experiments

Participants take back to work place DSP software

Description of Course

This combined theory and practice course provides an introduction to the principles of digital signal processing including the areas of discrete-time spectral analysis and adaptive signal processing. The course begins with an introduction to discrete-time signals and systems and continues with a lecture on digital filters, the FFT, random signal processing, direct and parametric methods for digital spectral analysis, linear prediction, and adaptive LMS algorithms. Computer experiments using a DSP software package on the PC will give participants the opportunity to generate, process, and analyze signals. Each participant will get a set of notes for the class sessions, and a copy of the DSP educational software package for the laboratory (experimental) portion. 

Who Should Attend

The course is designed for engineers, scientists,  and managers who need to understand the fundamental theory and applications of DSP. The course should be of particular interest to engineers who need to prepare for projects that involve DSP hardware and software. Participants should have an understanding of basic engineering science concepts. Familiarity with an IBM PC compatible though not mandatory it will be benefiscial. 

Course Content

Introduction to signals and linear systems: continuous and discrete time signals, time and frequency domain analysis, Fourier representations, uniform sampling, quantization issues, linear systems, frequency response, convolution and impulse response, stability considerations - z-transform: region of convergence, properties, inverse z-transform, transfer function, poles-zeros and stability, z transform and linear systems - digital filters: FIR and IIR digital filter realizations, transfer function and frequency response, linear phase FIR filters, FIR and IIR filter design, Butterworth, Chebychev, and Elliptic designs, Multirate DSP,  QMF banks and applications to sub-band coding,  the bilinear transform - Discrete and Fast Fourier Transform: properties and important transform pairs, time and frequency windows, circular and linear convolution, implementation issues, Applications of FFT to speech and other signals - Random signal processing fundamentals: stationary and ergodic signals, mean, variance, autocorrelation, cross-correlation, power spectral density, white noise, response of linear systems to random inputs - Direct and Parametric Methods for Spectral Analysis: estimators, periodograms and correlograms, ARMA, AR, and MA models for parametric spectral estimation, linear prediction, Levinson algorithm, Applicationsof linear prediction   to speech processing,  adaptive signal processing: least squares, system identification, adaptive gradient algorithms, the LMS algorithm, the RLS algorithm, sequential and block algorithms, frequency-domain algorithms, adaptive noise and echo cancellation, applications to equalizers and smart antennas.

Computer (Hands-On) Laboratory Exercises :

• Lab 1: filtering and convolution,

• Lab 2: z-transforms/transfer functions and frequency response

• Lab 3: FIR and IIR Filter Design

• Lab 4: Up-sampling and downsampling.QMF

• Lab 5: FFT and its applications,

• Lab 6: Linear prediction and adaptive filtering

Agenda (Course meets 8:15 am - 5 pm)

For Registration Information Contact: cysip@aol.com