This new algorithm is used for the synthesis of an associative memory implemented by a recurrent neural network with the connection matrix having upper bounds on the diagonal elements to reduce the total number
Book 2000, Soft Computing and Intelligent SystemsS.K. BASU Review article Pattern segmentation in a binary/analog world: unsupervised learning versus memory storing Associative memory is by now a well-established model of memory encoding and retrieval. According to this paradigm, data of long-term ...
is proposed to account for learning nonlinear types of association. The model (denoted as the MF-BAM) is composed of two modules, the Multi-Feature extracting bidirectionalassociative memory(MF), which contains various unsupervised network layers, and a modified Bidirectional Associative Memory (BAM),...
Kaburlasos, V.G.: Towards a Unified Modeling and Knowledge-Representation Based on Lattice Theory: Computational Intelligence and Soft Computing Applications. Studies in Computational Intelligence. Springer, New York (2006) Google Scholar Kaburlasos, V.G., Papadakis, S.E.: A granular extension ...
The performance of the FCMAC-CRI(S) is benchmarked against that of the Cox’s proportional hazard model and GenSoFNN-CRI(S) network, a functional hippocampal fuzzy semantic learning memory structure, in predicting bank failures based on a population of 3635 US banks observed over 21 years. ...
This modification is to increase the performance of associative memory neural network by avoiding most of the Hopfield neural network limitations. In general, MCA is a single layer neural network uses auto-association tasks and working in two phases, that is learning and convergence phases. MCA ...
A network for implementing the new framework is proposed in this paper. Simulations using similar/different patterns are done to show the unique feature of the proposed network.T.FuruhashiY.hattoriY.UchikawaInternational conference on soft computing...
Association Rule Miningfrequent pattern miningartificial neural networkautoassociativememorycorrelation matrix memoryAims: Frequent pattern mining is one of the imperative tasks in the data mining. The soft computing techniques such as neural network, fuzzy logic have potential to be used in frequent ...
In this paper, we investigate the stability of patterns embedded as the associative memory distributed on the complex-valued Hopfield neural network, in which the neuron states are encoded by the phase values on a unit circle of complex plane. As learning schemes for embedding patterns onto the ...
A set associative cache memory, comprising: an array of storage elements arranged as M sets by N ways; an allocation unit that allocates the storage elements in response to memory a