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 ...
Notes on Neural Computing and Associative Memory 333 A Numerical Example: Taxonomy(Hierarchical Clustering) of It is even possible to per- form a kind of numerical taxonomy on this that the " images" of different items are related according to a taxonomic graph where the 被引量: 6 年份: ...
LTP plays its role in memory or learning by changing the synaptic weight more persistently. LTP can last longer from minutes to days or even years. The process of memory formation in the brain (from sensory memory (SM) to STM and finally to LTM) can be aided by repeated rehearsal or tra...
This paper describes the strategy for implementation of Hopfield neural network as associative memory with the genetic algorithm and the Monte Carlo-(MC-) ... S Kumar,R Goel,MP Singh - 《Advances in Intelligent & Soft Computing》 被引量: 5发表: 2012年 加载更多研究...
In this paper we introduce the class of fuzzy kernel associative memories (fuzzy KAMs). Fuzzy KAMs are derived from single-step generalized exponential bidirectional fuzzy associative memories by interpreting the exponential of a fuzzy similarity measure
Steinbuch, K.: Die lernmatrix. Kybernetik1(1), 36–45 (1961). In German MATHGoogle Scholar Sudo, A., Sato, A., Hasegawa, O.: Associative memory for online learning in noisy environments using self-organizing incremental neural network. IEEE Trans. Neural Netw.20(6), 964–972 (2009) ...
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...
Hopfield neural networkpseudo-orthogonalizationcomplex numbersquaternionsHebbian learning rule is well known as a memory storing scheme for associative memory models. This scheme is simple and fast, however, its performance gets decreased when memory patterns are not orthogonal each other. Pseudo-...
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 of spurious memory. The scheme is evaluated via a full scale simulator to diagnose the...
Hopfield networkBidirectional Associative Memory (BAM)The focus in this paper is on the proposal of guaranteed patterns in the training set for associative networks. All proposed patterns are pseudoortogonal and they also fulfil stability condition. Patterns were stored into the matrix using Hebb ...