s. The model of associative memory is proposed in this paper based on concept of association between images and associative search. This model may be used for connect concept of inference with associative processing in neural networks.

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of nearor overcapacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of ...

In physical implementations of associative memory, wiring costs play a significant role in shaping patterns of connectivity. In this study of sparsely-connected associative memory, a range of architectures is explored in search of optimal connection strategies which maximise pattern-completion performance, while at the same time minimising wiring costs. It is found that architectures in which t...

Neuron models of associative memory provide a new and prospective technology for reliable date storage and patterns recognition. However, even when the patterns are uncorrelated, the efficiency of most known models of associative memory is low. We developed a new version of associative memory with record characteristics of its storage capacity and noise immunity, which, in addition, is effectiv...

A model of the hippocampus is presented which forms rapid self -organized representations of input arriving via the perforant path, performs recall of previous associations in region CA3, and performs comparison of this recall with afferent input in region CA 1. This comparison drives feedback regulation of cholinergic modulation to set appropriate dynamics for learning of new representations i...

A new model for associative memory with discrete time is proposed, in which chaos is taken into account and moreover the internal state of neurons depends on the past history. The network itself can search for minima of the energy successively by using the wandering motion and co-operative phenomena. By using this model we can clearly discuss the mechanism or the dynamics of the wandering motio...

An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural associative memories and hidden Markov models. The hidden Markov models generate subword-unit transcriptions of the spoken words and provide them as input to the associative memory module. The associative memory module is a networ...

Abstract In online education, it is critical for the quality of education to evaluate and grade assignments or examinations that students upload system. However, time-consuming determine how well circuit drawings prepared digital logic course, which a fundamental course in computer engineering similar disciplines, are not only correct but also compatible with truth table. Content-addressable me...

This thesis is concerned with one important question in artificial neural networks, that is, how biologically inspired connectivity of a network affects its associative memory performance. In recent years, research on the mammalian cerebral cortex, which has the main responsibility for the associative memory function in the brains, suggests that the connectivity of this cortical network is far ...

A sparsely connected associative memory model is tested with different pattern sets, and it is found that pattern recall is highly dependent on the type of patterns used. Performance is also found to depend critically on the connection strategy used to build the networks. Comparisons of topology reveal that connectivity matrices based on Gaussian distributions perform well for all pattern types...