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AbstractOne of the simplest associative memories is the Willshaw Network (Willshaw, Buneman &amp; Longuet-Higgins, 1969). Like other associative networks however (e.g., Hopfield, 1982), it fails completely as a memory device as soon as its capacity is exceeded. Three methods of synaptic change are analysed, decay, ageing and depression, under which this catastrophic failure can be preempted and stability under continuous learning ensured. These methods allow a Willshaw Network to function as a short-term memory, with effective storage of a well-defined number of recent associations, accompanied by the progressive forgetting of older ones. Expressions for the shortterm capacity under each method are obtained in the sparse coding limit and validated via simulation.