Abstract
Associative neural network models are a commonly used methodology when investigating the theory of associative memory in the brain. Comparisons between the mammalian hippocampus and neural network models of associative memory have been investigated [7]. Biologically based networks are complex systems built of neurons with a variety of properties. Here we compare and contrast associative memory function in a network of biologically-based spiking neurons [14] with previously published results for a simple artificial neural network model [6]. We investigate biologically plausible implementations of methods for improving recall under biologically realistic conditions, such as a sparsely connected network.
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Hunter, R., Cobb, S., Graham, B.P. (2008). Improving Associative Memory in a Network of Spiking Neurons. In: Kůrková, V., Neruda, R., KoutnÃk, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_66
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DOI: https://doi.org/10.1007/978-3-540-87559-8_66
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