Abstract. Our work is concerned with finding optimum connection strategies in highperformance associative memory models. Taking inspiration from axonal branching in biological neur...
We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict ...
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Recently, networks have increased rapidly both in scale and speed. Problems related to the control and management are of increasing interest. The average throughput and end-to-end ...
Recent research has shown that while many complex networks follow a power-law distribution for their node degrees, it is not sufficient to model these networks based only on their...