PhD Thesis #9107
|Delicate Nets, Faint Recollections: a Study of Partially Connected Associative Network Memories.
|This thesis explores partially connected networks in associative memory tasks. The storage capacity of the fully connected associative net is reviewed. Simulation results demonstrate that the performance of this architecture was worse than that predicted by earlier analyses. new analysis is presented that accurately describes the behaviour of this net. A characterization of the storage capacity and information efficiency of the partially connected associative net is presented. In partially connected nets, one of the key problems is how to set the unit thresholds in such a way that the units which should not fire are quiet and those that should fire do so. New thresholding strategies are developed which enable this architecture to function well as an associative content-addressable memory. An important result is that the best thresholding strategies are functions of the firing history of an output unit and the number of active inputs impinging on it. Analysis is presented that predicts the behaviour of single and multi-layer partially connected nets using the best thresholding strategy. It shows that for a large range of parameters values the information efficiency of the partially connected net is greater than that of both the fully connected associative net and simple competitive nets.
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