Approximation by neural networks and learning theory

We consider the problem of Learning Neural Networks from samples. The sample size which is sufficient for obtaining the almost-optimal stochastic approximation of function classes is obtained. In the terms of the accuracy confidence function, we show that the least-squares estimator is almost-optimal for the problem. These results can be used to solve Smale's network problem.