Some New Approaches to the Construction and Learning of Artificial Neural Networks

We propose two new approaches to the construction of artificial neural networks: a Fourier neural network and a binary neural network. A distinctive feature of the approaches proposed is the availability of simple, linear, single-step learning algorithms, which enables one to apply them to the construction of networks with a fairly large number of neurons and weights.