Signal Processing is a broad and growing discipline concerned with the manipulation and analysis of both analog and digital (sampled and quantized) signals. For example, a common use of both analog and digital processing is for filtering electrical signals to remove unwanted noise or to separate one signal from another. Examples of more sophisticated uses of signal processing arise in the formation of an X-ray CT image for medical diagnosis, or in machine recognition and synthesis of speech. Increasingly sophisticated uses of signal processing have appeared in these areas and in many others, including communications, control, image and video processing, radar, sonar, geophysical exploration, and consumer electronics. This expanded use of signal processing techniques has been prompted by advances in both the mathematical theory and the physical devices used for signal processing. This is especially true for digital signal processing, where sampled and quantized analog signals are processed using computers or special-purpose digital hardware.
The field of signal processing includes the mathematical theory of the subject as well as the design and analysis of the necessary devices for carrying out the processing. Undergraduates desiring a specialization in signal processing should consider the electives listed below, which range from theoretical courses in digital signal processing, communications, control systems, and mathematics, to more implementation-oriented courses in circuits and computers.
* Students planning on graduate work should consider taking Math 418 in place of Math 415 and either Math 444 or Math 447.
For additional information and advice, please contact any faculty member of the Signal and Image Processing Group: Professors Richard E. Blahut, Y. Bresler, C. Hadjicostis, M. Hasegawa-Johnson, T. S. Huang, D. L. Jones, S. E. Levinson, Z-P Liang, P. Moulin, Naresh R. Shanbhag, and Andrew C. Singer.