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Rensselaer Polytechnic Institute

Digital Signal Processing

This course provides a comprehensive treatment of the theory, design, and implementation of digital signal processing algorithms. In the first half of the course, we emphasize frequency-domain and Z-transform analysis. In the second half of the course, we investigate advanced topics in signal processing, including multirate signal processing, filter design, adaptive filtering, quantizer design, and power spectrum estimation. The course is fairly application-independent, to provide a strong theoretical foundation for future study in communications, control, or image processing.

Instructor

Professor Richard Radke.

Electronics

2014

Lecture 01 - Signals

Lecture 02 - Linear, Time-invariant Systems

Lecture 03 - Convolution and its Properties

Lecture 04 - The Fourier Series

Lecture 05 - The Fourier Transform

Lecture 06 - Frequency Response

Lecture 07 - The Discrete-time Fourier Transform

Lecture 08 - Introduction to the z-Transform

Lecture 09 - Inverse z-Transform; Poles and Zeros

Lecture 10a - Exam 1 Review

Lecture 10 - The Discrete Fourier Transform

Lecture 11 - Radix-2 Fast Fourier Transforms

Lecture 12 - The Cooley-Tukey and Good-Thomas FFTs

Lecture 13 - The Sampling Theorem

Lecture 14 - Continuous-time Filtering with Digital Systems; Upsampling and Downsampling

Lecture 15 - Multirate Signal Processing and Polyphase Representations

Lecture 16 - FIR Filter Design using Least-Squares

Lecture 17 - FIR Filter Design (Chebyshev)

Lecture 18 - IIR Filter Design

Lecture 19 - Introduction to Adaptive Filtering: ARMA Processes

Lecture 20 - The Wiener Filter

Lecture 21 - Gradient Descent and LMS

Lecture 22a - Exam 2 Format/ Review

Lecture 22 - Least Squares and Recursive Least Squares

Lecture 23 - Introduction to Quantization

Lecture 24 - Differential Quantization and Vocoding

Lecture 25 - Perfect Reconstruction Filter Banks and Introduction to Wavelets