  Artificial neural networks (ANN) are inadequate to biological neural
networks. This inadequacy is manifested in the use of the obsolete model of the
neuron and the connectionist paradigm of constructing ANN. The result of this
inadequacy is the existence of many shortcomings of the ANN and the problems of
their practical implementation. The alternative principle of ANN construction
is proposed in the article. This principle was called the detector principle.
The basis of the detector principle is the consideration of the binding
property of the input signals of a neuron. A new model of the neuron-detector,
a new approach to teaching ANN - counter training and a new approach to the
formation of the ANN architecture are used in this principle.
