Augmentation of pattern matching with divergence histograms
Abstract:
A processor may apply data blocks of a training data set to a pattern matching algorithm to identify whether the data blocks match a pattern, determine points of divergence between the data blocks and the pattern, count a number of times that each of a plurality of positions in the pattern is determined to be a point of divergence, and determine a position with a highest count of a number of times that the position is determined to be a point of divergence. The processor may further receive an incoming data block, compare a data value at the position in the pattern with the highest count to a data value at a corresponding position in the incoming data block, and determine a mismatch when the data value at the position in the pattern and the data value at the corresponding position in the incoming data block are different.
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