Spike-Based Sensing and Processing (Profile)
Dr. John G. Harris co-directs the Computational NeuralEngineering Lab (CNEL) at the University of Florida, together with its founder: Dr. Jose C. Principe. CNEL seeks to advance the theory and applications of adaptive systems using mathematics and anthropomorphic principles. This work is highly multidisciplinary and of broad impact since it is geared to provide new engineering design principles. Analogies from biology are expressed in appropriate mathematical frameworks and implemented in digital algorithms or directly in analog VLSI chips. Since its inception in 1992, the CNEL has created an international reputation in the areas of adaptive filtering theory, artificial neural networks, nonlinear dynamics, neuromorphic engineering, and more recently in brain machine interfaces and information theoretic learning. 1. Incredible fault tolerance: the brain loses an average of 10,000 neurons per day without requiring any sort of explicit reconfiguration or rewiring. 2. Ultra-low power consumption: The brain consumes an average of 12 Watts, much less than a typical Pentium computer performing much less computation. Fig. 2. Experimental 32x32 pixel time-to-first-spike imager.