memory-based model

Algorithms {memory-based models} (MBM) can match input-pattern components to template-pattern components, using weighted sums, to find highest scoring template. Scores are proportional to similarity. Memory-based models uniquely label component differences. Memory-based recognition, sparse-population coding, generalized radial-basis-function (RBF) networks, and hyper-basis-function (HBF) networks are similar algorithms.

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Date Modified: 2022.0224