Welcome to SSPACISS: Statistical Signal Processing Applied to Cochlear Implants and Subsurface Sensing
Our research is in the area of physics-based statistical signal processing algorithms, and we are actively engaged in two general application areas: (1) Investigating human perception and developing robust remediation strategies for a variety of communication impairments or limitations; (2) developing robust sensor-based algorithms for the remote detection and identification of potentially hazardous buried objects, such as unexploded ordnance (UXO) and landmines. Our research methodology is distinguished in two fundamental ways. First, we place an emphasis on incorporating the physics or phenomenology that governs the specific application directly into the signal processing framework, and we consider both experimental and theoretical issues. Second, we maintain a close and highly interactive collaboration with the end-user community that provides necessary feedback to the development process and validates the real-world utility of our research efforts. Our work in these application areas has improved quality of life and safety of life as a result of the development of novel signal processing algorithms.
Signal processing algorithms perform best when the physics that define the problem are integrated within the mathematical constructs underlying the theory of signal processing. ~S. Haykin, 2001
Utilizing experimental data measured under realistic conditions to test the performance of algorithms, and using insight from the data to guide the algorithm development process is a relatively new focus within traditional signal processing research. This is the approach that we have pursued in the context of our signal processing research. Our work is tightly coupled to the phenomenology associated with our application areas of interest, and the proof of performance always relies on processing or predicting realistic experimental data measured in true-to-life scenarios.