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Artificial neural networks (ANN) are inadequate to biological neuralnetworks. This inadequacy is manifested in the use of the obsolete model of theneuron and the connectionist paradigm of constructing ANN. The result of thisinadequacy is the existence of many shortcomings of the ANN and the problems oftheir practical implementation. The alternative principle of ANN constructionis proposed in the article. This principle was called the detector principle.The basis of the detector principle is the consideration of the bindingproperty 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 theformation of the ANN architecture are used in this principle.

The detector principle of constructing artificial neural networks as an alternative to the connectionist paradigm