Shift invariant pattern recognition by associative memory

Presents a network architecture that can perform shift invariant pattern recognition. The network is composed of a preprocessing block and an associative memory block which is a recurrent neural network. The preprocessing network is designed in such a way that the output of this block is almost invariant under shifted input patterns. The associative memory block is employed to recall the original patterns stored in the system. A step by step design procedure for realizing shift invariant pattern recognition is provided.<
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