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Browsing by Author "Chen, W."
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Clustering predicts memory performance in networks of spiking and non-spiking neurons
Chen, W.; Maex, R.; Adams, R.G.; Steuber, Volker; Calcraft, L.; Davey, N. (2011)The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in ... -
Connection Strategies in Associative Memory Models
Chen, W.; Maex, R.; Adams, R.G.; Calcraft, L.; Steuber, Volker; Davey, N. (2009)The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so results in artificial ... -
Connectivity graphs and the performance of sparse associative memory models
Chen, W.; Adams, R.G.; Calcraft, L.; Steuber, Volker; Davey, N. (Institute of Electrical and Electronics Engineers (IEEE), 2008) -
High capacity associative memory with bipolar and binary, biased patterns
Chen, W.; Adams, R.G.; Calcraft, L.; Davey, N.; Steuber, Volker (2007)The high capacity associative memory model is interesting due to its significantly higher capacity when compared with the standard Hopfield model. These networks can use either bipolar or binary patterns, which may also ... -
The Performance of Associative Memory Models with Biologically Inspired Connectivity
Chen, W. (2009-04-01)This thesis is concerned with one important question in artificial neural networks, that is, how biologically inspired connectivity of a network affects its associative memory performance. In recent years, research on the ... -
Update thresholds and high capacity associative memories.
Chen, W.; Adams, R.G.; Calcraft, L.; Davey, N. (2006)It has been found that the performance of an associative memory model trained with the perceptron learning rule can be improved by increasing the learning threshold. When the learning threshold increases, the range of ... -
Using graph theoretic measures to predict the performance of associative memory models
Calcraft, L.; Adams, R.G.; Chen, W.; Davey, N. (ESANN, 2008)We test a selection of associative memory models built with different connection strategies, exploring the relationship between the structural properties of each network and its pattern-completion performance. It is found ...