a note about course materials
My more recent course materials is now on WPI's Canvas learning management system. Older course materials can be found below.
ece4703: real-time dsp
This course provides a basic introduction to the principles of real-time digital signal processing (DSP). Topics include: design of real-time DSP architectures, sampling and quantization of continuous time signals, design and implementation of FIR and IIR digital filters, and theory and application of the Fast Fourier Transform (FFT). The emphasis of the course is on the design and implementation of DSP algorithms. The algorithms are implemented on personal, portable DSP boards that the students can either program in the lab or purchase for use on their home computers. This course features an interactive studio format with mini-lectures and labs integrated into three-hour sessions. This format allows the students to try out the algorithms and methods shown in class immediately, with the instructor nearby to lend assistance and advice. Recommended background: ECE 2312 experience in C programming.
ece2305: introduction to communications and networking
This course provides an introduction to the broad area of communications and networking, providing the context and fundamental knowledge appropriate for all electrical and computer engineers, as well as for further study in this area. The course is organized as a systems approach to communications and networking. Topics include fundamental definitions and concepts (bandwidth, information, etc.), types of transmission media, conversion between the analog and digital domains, switching and networking principles and architectures, wireless networking, networking protocols, regulatory and applications issues. Recommended background: ECE 2011.
ece503: digital signal processing
ECE503 is a first-year graduate course on the analysis of and simulation of discrete-time signals and systems. The topics covered in this course include: discrete-time signals and systems, frequency analysis, sampling of continuous-time signals, the z-transform, implementation of discrete-time systems, the discrete Fourier transform, fast Fourier transform algorithms, filter design techniques, finite precision effects, and multirate signal processing. Students taking this course should have previously completed an undergraduate-level course on discrete-time signals and systems as well as a course in complex variables. This course also assumes some familiarity with Matlab.
The Spring 2019 offering of this course is available on WPI Canvas.
ece531: principles of detection and estimation theory
The subject of signal detection and estimation is concerned with the processing of information-bearing signals for the purpose of making inferences about the information that they contain. The purpose of this course is to provide an introduction to the fundamental theoretical principles underlying the development and analysis of techniques for such processing. The level of this course is suitable for research students in communications, control, signal processing, and related areas. Students taking ECE531 should have a background in probability and random processes (ECE502 or equivalent; may be taken concurrently) and a familiarity with dynamic systems (ECE504 or equivalent).
ece2311: continous-time signal and system analysis
This course provides an introduction to time and frequency domain analysis of continuous time signals and linear systems. Topics include signal characterization and operations; singularity functions; impulse response and convolution; Fourier series; the Fourier transform and its applications; frequency-domain characterization of linear, time-invariant systems such as filters; and the Laplace transform and its applications.
ece504: analysis of deterministic signals and systems
ECE504 is a first-year graduate course on the analysis of deterministic continuous-time and discrete-time signals and systems. The topics covered in this course form a foundation for several applied disciplines including control systems, signal processing, and communication systems. The primary goals of this course are to provide an understanding of the fundamentals that govern the behavior of continuous-time and discrete-time dynamic systems and to provide the student with a sophisticated set of tools for analyzing systems. From a top level perspective, this course addresses three core subjects: (i) mathematical description of signals and systems, (ii) qualitative and quantitative analysis of systems, and (iii) design/modification of systems to meet performance criteria. The focus of this course is primarily theoretical, but illustrative examples and computer exercises will be used liberally to develop intuition and reinforce the core concepts.
ieee texas instruments real-time dsp workshop (oct 19-20, 2009)
handouts
How to correctly install the Code Composer Studio v3.1 IDE.
example code
Example code for stereo loop..
Example code for stereo FIR filtering.
A better example project for stereo FIR filtering with a 73 coefficient bandpass filter and array index updating rather than moving data.
Example code for IIR filtering. Unzip this file into the c:\myproject\workshop directory. Note that there are three source files in this project - one for Direct Form I, one for Direct Form II, and the last for Direct Form II with Second Order Sections. All of the math is single-precision float but this can be modified. Add/remove source files to try each realization structure.
additional files
TMS320C6713B datasheet.
Filter coefficients for FIR filter example.
Filter coefficients for IIR Direct Form I filter example.
Filter coefficients for IIR Direct Form II filter example.
Filter coefficients for IIR Direct Form II with Second Order Sections filter example.
ece4304: communication systems engineering
This course introduces the theory and performance analysis of communication in noise. The mathematical treatment of noise as a random process is developed in the context of baseband and passband transmission systems. The performance of analog transmission systems is developed and the tradeoff between bandwidth and performance is exposed. The optimum PCM receiver is derived and introduces the general concept of decision theory and signal space representation of decision systems. A treatment of coding theory for error detection, correction and compression leads to the development of Shannon's information theory and the ultimate performance of digital transmission systems. Finally, concepts that underly modern digital data computer network systems are introduced. Recommended background: ECE 3311 and MA 2621.