Digital Signal Processing
Faculty advisors:
Digital signal processing became possible when digital computers came into existance and then became cheap enough to be considered components. Almost all the classical analog signal processing applications (like telephones, radio sets, signal generators, and oscilloscopes) can now be done digitally. DSP is done in real time or offline; it is done on such one-dimensional signals as audio, and such two-dimensional signals as images. Embedded processors for doing DSP are found in cell phones, audio players, digital cameras, automobile engines, braking control systems, and medical instruments. Examples of applications on large computers include seismic exploration, geophysical mapping, motion picture animation, and medical imaging. The range of applications is enormous.
To study digital signal processing, it is necessary to have a good grounding in discrete-time linear systems and time-frequency transformations. The essential prerequisite for the senior DSP theory and lab courses is the Linear Systems core course. In addition, real-time applications require experience with assembly language code development. Offline processing requires the use of high-level application languages like MATLAB. DSP is a good area for those who enjoy the design and development of algorithms, applied mathematics, and applications. Students who intend to complete degrees in both EE and music will find the DSP lab course especially interesting.
Representative Technical Applications
- Audio generation, coding, reproduction, and enhancement
- Image processing, enhancement, coding, and pattern recognition
- Video analysis, coding and decoding
- Wireless communications modulation and demodulation
- The design of dedicated DSP processors
- The use of DSP in feedback control
Representative Societal Applications
- Aids for human speech and hearing
- Aids for human vision
- Medical instruments which can see into the body and the brain
- Environmental analysis using remote sensing data
