Digital Signal Processing Video Lectures

Course Description

This course was developed in 1987 by the MIT Center for Advanced Engineering Studies. It was designed as a distance-education course for engineers and scientists in the workplace.

Advances in integrated circuit technology have had a major impact on the technical areas to which digital signal processing techniques and hardware are being applied. A thorough understanding of digital signal processing fundamentals and techniques is essential for anyone whose work is concerned with signal processing applications.

Digital Signal Processing begins with a discussion of the analysis and representation of discrete-time signal systems, including discrete-time convolution, difference equations, the z-transform, and the discrete-time Fourier transform. Emphasis is placed on the similarities and distinctions between discrete-time. The course proceeds to cover digital network and non-recursive (finite impulse response) digital filters. Digital Signal Processing concludes with digital filter design and a discussion of the fast Fourier transform algorithm for computation of the discrete Fourier transform.

Instructors:

Prof. Alan V. Oppenheim

Video Lectures:

Demonstration 1: Sampling, Aliasing, and Frequency Response, Part 1. (Go to this video)

Demonstration 2: Sampling, Aliasing, and Frequency Response, Part 2. (Go to this video)

Lecture 1: Introduction. (Go to this video)

Lecture 2: Discrete-Time Signals and Systems, Part 1. (Go to this video)

Lecture 3: Discrete-Time Signals and Systems, Part 2. (Go to this video)

Lecture 4: The Discrete-Time Fourier Transform. (Go to this video)

Lecture 5: The z-Transform. (Go to this video)

Lecture 6: The Inverse z-Transform. (Go to this video)

Lecture 7: z-Transform Properties. (Go to this video)

Lecture 8: The Discrete Fourier Series. (Go to this video)

Lecture 9: The Discrete Fourier Transform. (Go to this video)

Lecture 10: Circular Convolution. (Go to this video)

Lecture 11: Representation of Linear Digital Networks. (Go to this video)

Lecture 12: Network Structures for Infinite Impulse Response (IIR) Systems. (Go to this video)

Lecture 13: Network Structures for Finite Impulse Response (FIR) Systems and Parameter Quantization Effects in Digital Filter Structures. (Go to this video)

Lecture 14: Design of IIR Digital Filters, Part 1. (Go to this video)

Lecture 15: Design of IIR Digital Filters, Part 2. (Go to this video)

Lecture 16: Digital Butterworth Filters. (Go to this video)

Lecture 17: Design of FIR Digital Filters. (Go to this video)

Lecture 18: Computation of the Discrete Fourier Transform, Part 1. (Go to this video)

Lecture 19: Computation of the Discrete Fourier Transform, Part 2. (Go to this video)

Lecture 20: Computation of the Discrete Fourier Transform, Part 3. (Go to this video)

Lecture Notes:

LEC #	TOPICS	LECTURE NOTES	PROBLEM SOLUTIONS
1	Introduction	(PDF)
2	Discrete-time signals and systems, part 1	(PDF)	(PDF)
3	Discrete-time signals and systems, part 2	(PDF)	(PDF)
4	The discrete-time Fourier transform	(PDF)	(PDF)
5	The z-transform	(PDF)	(PDF)
6	The inverse z-transform	(PDF)	(PDF)
7	Z-transform properties	(PDF)	(PDF)
8	The discrete Fourier series	(PDF)	(PDF)
9	The discrete Fourier transform	(PDF)	(PDF)
10	Circular convolution	(PDF)	(PDF)
11	Representation of linear digital networks	(PDF)	(PDF)
12	Network structures for infinite impulse response (IIR) systems	(PDF)	(PDF)
13	Network structures for finite impulse response (FIR) systems and parameter quantization effects in digital filter structures	(PDF)	(PDF)
14	Design of IIR digital filters, part 1	(PDF)	(PDF)
15	Design of IIR digital filters, part 2	(PDF)	(PDF)
16	Digital Butterworth filters	(PDF)	(PDF)
17	Design of FIR digital filters	(PDF)	(PDF)
18	Computation of the discrete Fourier transform, part 1	(PDF)	(PDF)
19	Computation of the discrete Fourier transform, part 2	(PDF)	(PDF)
20	Computation of the discrete Fourier transform, part 3	(PDF)	(PDF)

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