A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
The present invention was made with government support under the following government grants or contracts: Office of Naval Research Grant Nos. N00014-06-1-0769, N00014-06-1-0829 and N00014-02-1-0353, U.S. Department of Energy Grant No. DE-FC02-01ER25462, and National Science Foundation Grant Nos. ANI-0099148, ANI-0099148 and IIS-0625717. The government has certain rights in the invention.