Abstract
In the neural network theory content-addressable memories are defined by patterns that are attractors of the dynamical rule of the system. This paper develops a quantum neural network starting from a classical neural network Hamiltonian and using a Schrödinger-like equation. It then shows that such a system exhibits probabilistic memory storage characteristics analogous to those of the dynamical attractors of classical systems.
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Bonnell, G., Papini, G. Quantum neural network. Int J Theor Phys 36, 2855–2875 (1997). https://doi.org/10.1007/BF02435714
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DOI: https://doi.org/10.1007/BF02435714