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Clustering predicts memory performance in networks of spiking and non-spiking neurons
(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
(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 ...
Connection strategy and performance in sparsely connected 2D associative memory models with non-random images
(2009)
A sparsely connected associative memory model is tested with different pattern sets, and it is found that pattern recall is highly dependent on the type of patterns used. Performance is also found to depend critically on ...
Connectivity graphs and the performance of sparse associative memory models
(Institute of Electrical and Electronics Engineers (IEEE), 2008)
Using graph theoretic measures to predict the performance of associative memory models
(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 ...
Efficient connection strategies in 1D and 2D associative memory models with and without displaced connectivity
(2008)
This study examines the performance of sparsely connected associative memory models built using a number of different connection strategies, applied to one- and two-dimensional topologies. Efficient patterns of connectivity ...
Sparsely-connected associative memory models with displaced connectivity.
(2007)
Our work is concerned with finding optimum connection strategies in high-performance associative memory models. Taking inspiration from axonal branching in biological neurons, we impose a displacement of the point of ...
High capacity associative memory with bipolar and binary, biased patterns
(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 ...