  This paper highlights the possibility of creating quantum neural networks
that are trained by Grover's Search Algorithm. The purpose of this work is to
propose the concept of combining the training process of a neural network,
which is performed on the principles of Grover's algorithm, with the functional
structure of that neural network, interpreted as a quantum circuit. As a simple
example of a neural network, to showcase the concept, a perceptron with one
trainable parameter - the weight of a synapse connected to a hidden neuron.
