By Vasantha Kalyani David

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Extra info for Pattern Recognition using Neural and Functional Networks

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Complement Coding Input patterns are normalized by complement coding, a preprocessing step that solves potential fuzzy ART category proliferation problem [16], [56], [57], [58], [63], [64]. Complement coding in neurobiological terms uses both on-cells and off cells to represent an input pattern and preserves individual feature amplitudes while normalizing the total on-cell / off-cell activity. The features that are critically present in category exemplars are encoded by the on-cell portion of a prototype.

WjN b ) denotes the weight vector for th ab the j node to F . The system resets xa , ya , xb , yb , xab to 0 between input presentations. Re The map field Fab receives input from either or both of the ARTa and ARTb category fields. A chosen Fa2 node J sends input to the map field Fab via the weights wjab . Active Fb2 node K sends input to Fab via one-to-one pathways between Fb2 and Fab . If both ARTa and ARTb are active, Fab remains active only if ARTa predicts the same category as ARTb . The Fab output vector xab obeys the following.

When the system chooses the Jth category then yJ = 1 and yj = 0 for j = J. 6) ⎩ I ∧ w if Jth F node node is chosen. J 2 Resonance or Reset ct J| If the subsethood match function |I∧w of the chosen category meets the vigilance |I| criterion as follows then resonance occurs. 10) Re | x |=| I ∧ wJ |≥ ρ | I | mismatch reset occurs if and thus if The system then sets the value of the choice function. TJ to 0 for the duration of the input presentation to prevent the persistent selection of the same category during search.

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