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...
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 ...
Index-based reservoir-computing memory In the “location-addressable” or “parameter-addressable” scenario, the stored memory states within the neural network are activated by a specific location address or an index parameter. The stimulus that triggers the system to switch states can be entirely ...
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 ...
1977). The BSB could perform auto-association by storing patterns in attractors that were produced by nonlinear recurrent feedback within its network. Consequently, the BSB inspired a new subclass of NAMs, referred to as recurrent neuralassociative memory(RNAM), mainly interested in the neurodynamic...
In this paper, some new estimation results on the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to m... J Cao,Q Tao - 《Physics Letters A》 被引量: 152发表: 2001年 A new synthesis approach for feedback neural networks based on the pe...
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. ...
12. A reduction processor according to claim 3, wherein several of said first order reduction processors are connected in a hierarchy of networks, each network being a ring (FIG. 39). 13. A reduction processor according to claim 1, wherein each storage cell (2; 10; FIG. 4A, FIG. 4E...
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 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