In this paper, we propose a new multi-comparand associative machine (MCA-machine) and its application to relational algebra operations. We first offer a new efficient associative algorithm for the multi-comparand parallel search. It generalizes the Falkoff associative algorithm that performs a parallel search in a matrix based on the exact match with a given pattern. Then we apply the new assoc...

in this paper, a bidirectional associative memory (bam) neural network, which consists of two neurons in the x-layer and three neurons in the y-layer, with two time delays will be studied. we conclude that under some assumptions, hopf bifurcation occurs when the sum of two delays passes through a critical value. a numerical example is presented to support our theoretical results.

This paper discusses the realization of a quantum associative memory using linear integrated optics. An associative memory produces a full pattern of bits when presented with only a partial pattern. Quantum computers have the potential to store large numbers of patterns and hence have the ability to far surpass any classical neural network realization of an associative memory. In this work two ...

This paper proposes a probabilistic model for associative anaphora resolution in Japanese. Associative anaphora is a type of bridging anaphora, in which the anaphor and its antecedent are not coreferent. Our model regards associative anaphora as a kind of zero anaphora and resolves it in the same manner as zero anaphora resolution using automatically acquired lexical knowledge. Experimental res...

In this research paper, a novel Convolutional Associative Memory is proposed. In the proposed model, Synapse of each neuron is modeled as a Linear FIR filter. The dynamics of Convolutional Associative Memory is discussed. A new method called SubSampling is given. Proof of convergence theorem is discussed. An example depicting the convergence is shown. Special cases to the proposed convolutional...

We consider application of neural associative memories to chemical image recognition. Chemical image recognition is identification of substance using chemical sensors' data. The primary advantage of associative memories as compared with feed-forward neural networks is highspeed learning. We have made experiments on odour recognition using hetero-associative and modular autoassociative memories....