Distributed processing in frames for sparse approximation

13 years 10 months ago

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—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit inherent redundancy. In many cases, these systems are required to use distributed computational strategies to analyze and process the sensory information. In this talk, I will review the use of frames to model distributed sensing systems with a particular focus on sensory neural systems. In light of the evidence that many of these systems employ sparse codes, I will describe our Locally Competitive Algorithms (LCAs) that use a dynamical system to solve many sparse approximation problems. These LCAs employ a parallel computational architecture with simple analog components. I will show numerical simulation results for these systems and describe their relationship to the many recently-proposed iterative thresholding algorithms. Our LCA approach also demonstrates potential advantages in coding time-varying signals...

Christopher J. Rozell

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