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- W2133503316 abstract "A high-gain, post-annealing, generalized Hebbian algorithm is proposed and observed to have chaotic learning behavior. It lends itself readily to a highly efficient parallel distributed architecture for principal components computation. The work is extended to a convergence accelerator that uses the chaotic pattern learned during the first few epochs for an iterative weight-change procedure. Applications of using the parallel architecture for image encoding, reconstruction, and matching are described. Successful simulation results in yielding good quality reconstructed images and photo/sketch matching are reported." @default.
- W2133503316 created "2016-06-24" @default.
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- W2133503316 date "2003-06-25" @default.
- W2133503316 modified "2023-09-26" @default.
- W2133503316 title "Image coding/reconstruction and matching using a parallel distributed Hebbian architecture" @default.
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- W2133503316 doi "https://doi.org/10.1109/ijcnn.2002.1005607" @default.
- W2133503316 hasPublicationYear "2003" @default.
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