Signal Processing

Signal processing is a sub-discipline of electrical engineering that focuses on the acquisition, modeling, and interpretation of digital data. It is a powerful enabling technology used in a wide variety of products such as smartwatches, cell phones, hearing aids, and autonomous vehicles. 

Our areas of expertise include:

Ocean acoustic signal processing

The Ocean Acoustic Signal Processing research group investigates multi-disciplinary problems requiring a synthesis of array processing, underwater acoustics, and oceanography.  Current projects focus on random matrix theory, sparse array design, deep water ambient noise, and acoustic mode propagation in random media.  Our work enables performance prediction for adaptive sonar systems and develops new algorithms for analyzing underwater data sets. Principal investigator: Kathleen E. Wage.

Signal processing in communications and data science

This group is engaged in basic research on signal processing and wireless communications in the big-data era. Current research efforts focus on i) communications: wideband cognitive radios, 5G networks, and massive MIMO technology; ii) data science: high-dimensional structured signal and data analytics, statistical inference of network data, and distributed machine learning with communication efficiency and robustness. The common research threads in these areas are the emerging high-dimensional signals, large-scale networks, and huge-size problems fueled by hardware advances toward wideband RF terminals, massive IoT devices, and the availability of a large amount of data. These challenges call for new paradigms in signal acquisition, information processing, and machine learning, which constitute the motivation pillars of this group in pursuing novel solutions with high efficiency, performance, and robustness. Research is carried out jointly with  Xiang Chen’s group in the chartered SMART lab (Signal processing, Mobile computing, Artificial intelligence Research and Technology). Principal Investigators: Zhi Tian, Xiang Chen, Yue Wang.