  Magnetic tunnel junctions (MTJ) have been successfully applied in various
sensing application and digital information storage technologies. Currently, a
number of new potential applications of MTJs are being actively studied,
including high-frequency electronics, energy harvesting or random number
generators. Recently, MTJs have been also proposed in designs of a new
platforms for unconventional or bio-inspired computing. In the present work, it
is shown that serially connected MTJs forming a multi-state memory cell can be
used in a hardware implementation of a neural computing device. A behavioral
model of the multi-cell is proposed based on the experimentally determined MTJ
parameters. The main purpose of the mutli-cell is the formation of the
quantized weights of the network, which can be programmed using the proposed
electronic circuit. Mutli-cells are connected to CMOS-based summing amplifier
and sigmoid function generator, forming an artificial neuron. The operation of
the designed network is tested using a recognition of the hand-written digits
in 20x20 pixel matrix and shows detection ratio comparable to the software
algorithm, using the weight stored in a multi-cell consisting of four MTJs or
more.
