Abstract
Most associative memory work has concentrated on autoassociative memories (AAMs). These associative processors provide reduced noise and error correction in their output data. We will consider heteroassociative memories (HAMs), which are needed to provide decisions on the class of the input data and inferences for subsequent processing. We derive new equations for the storage capacity and noise performance of HAMs, emphasize how they differ from those derived for AAMs, suggest new performance measures to be used, and show how different recollection vector encodings can improve HAM performance.
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