Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Digital Signal Processing Lectures, Fall 2014

Rensselaer Polytechnic Institute via YouTube

Start learning Write review

Details

Start learning

Provider

YouTube
Pricing

Free Video
Languages

English
Effort

1 day 6 hours
Sessions

Self-Paced
Level

Intermediate

Found in

This lecture series introduces digital signal processing through signals and linear time-invariant systems, Fourier and z-transforms, sampling, FFTs, multirate processing, filter design, adaptive filtering, quantization, vocoding, filter banks, and wavelets. It also includes an introduction to MATLAB for DSP.

Syllabus

DSP Lecture 1: Signals.
DSP Lecture 2: Linear, time-invariant systems.
DSP Lecture 3: Convolution and its properties.
DSP Lecture 4: The Fourier Series.
DSP Lecture 5: the Fourier Transform.
DSP Lecture 6: Frequency Response.
DSP Lecture 7: The Discrete-Time Fourier Transform.
DSP Lecture 8: Introduction to the z-Transform.
DSP Lecture 9: Inverse z-Transform; Poles and Zeros.
DSP Lecture 10: The Discrete Fourier Transform.
DSP Lecture 10a: Exam 1 Review.
DSP Lecture 11: Radix-2 Fast Fourier Transforms.
DSP Lecture 12: The Cooley-Tukey and Good-Thomas FFTs.
DSP Lecture 13: The Sampling Theorem.
DSP Lecture 14: Continuous-time filtering with digital systems; upsampling and downsampling.
DSP Lecture 15: Multirate signal processing and polyphase representations.
DSP Lecture 16: FIR filter design using least-squares.
DSP Lecture 17: FIR filter design (Chebyshev).
DSP Lecture 18: IIR filter design.
DSP Lecture 19: Introduction to adaptive filtering; ARMA processes.
DSP Lecture 20: The Wiener filter.
DSP Lecture 22a: Exam 2 format/review.
DSP Lecture 21: Gradient descent and LMS.
DSP Lecture 22: Least squares and recursive least squares.
DSP Lecture 23: Introduction to quantization.
DSP Lecture 24: Differential quantization and vocoding.
DSP Lecture 25: Perfect reconstruction filter banks and intro to wavelets.
DSP Lecture 1a: Matlab for DSP; introduction to Cody Coursework.