  Recently, an associative memory operation by a virtual oscillator network,
consisting of a single spintronic oscillator, was examined to solve issues in
conventional, real oscillators-based neural networks such as inhomogeneities
between the oscillators. However, the spintronic oscillator still carries
issues dissipating large amount of energy because it is driven by electric
current. Here, we propose to use a single ferromagnet manipulated by
voltage-controlled magnetic anisotropy (VCMA) effect as a fundamental element
in a virtual neural network, which will contribute to significantly reducing
the Joule heating caused by electric current. Instead of the oscillation in
oscillator networks, magnetization relaxation dynamics were used for the
associative memory operation. The associative memory operation for alphabet
patterns is successfully demonstrated by giving correspondences between the
colors in a pattern recognition task and the sign of a perpendicular magnetic
anisotropy coefficient, which could be either positive or negative via the VCMA
effect.
