Nonlinear least squares method and block recurrent and iterative procedures in neural networks teaching

The article is devoted to the development of the feedforward neural networks teaching algorithms based on nonlinear least squares method with pseudo-inversion. Application of Cline block pseudoinversion formula to teaching algorithms based on weights vector decomposition is considered. This approach allows to decrease computational costs by virtue of pseudo-inversion of matrices of small size.