With small-scale quantum processors transitioning from experimental physics labs to
industrial products, these processors in a few years are expected to scale up and be more …

With small-scale quantum processors transitioning from experimental physics labs to
industrial products, these processors allow us to efficiently compute important algorithms in …

This paper presents the QAMDiagnos, a model of Quantum Associative Memory (QAM) that
can be a helpful tool for medical staff without experience or laboratory facilities, for the …

In view of the problem that Hopfield neural network is easy to fall into local minimum, this
paper proposes a modified Hopfield neural network to overcome this problem. By adjusting …

Recall operations of quantum associative memory (QuAM) have been conducted separately
through evolutionary as well as non-evolutionary processes in terms of unitary and non …

Abstract Using Singh-Rajput MES as memory states in the evolutionary process of pattern
storage and the non-evolutionary process of pattern recall (the two fundamental constituents …

In this paper, we design a quantum associative classifier, which includes pattern storage
and pattern classification. For pattern storage, we present a method to construct quantum …

New set of maximally entangled states (Singh-Rajput MES), constituting orthonormal eigen
bases, has been revisited and its superiority and suitability in pattern-association (Quantum …

The model of Quantum Associative Memories (QAM) we propose here consists in simplifying
and generalizing that of Rigui Zhou et al. which uses the quantum matrix with the binary …

This paper we proposed a quantum pattern search algorithm based on Grover's algorithm
with closed match. Compared to QuAM proposed by Dan Ventura and QuAM with distributed …