Neural network algorithms for determining the values of signal parameters in radio-electronic hardware

The paper proposes a general approach to the development of neural network algorithms for determining the values of signal parameters in radio-electronic, telecommunication, and information systems from the functional level to the level of nano-elements; the approach is based on the principles of data, image, and signal recognition. Implementation of this general approach is illustrated by a neural network algorithm developed to control the relative deviation of the chirp signal frequency from the linear law. We herein show possible ways to reduce the probability of errors and further improve the performance of neural network algorithms systems for automatic and technical control of signal parameters at all functional and structural levels of radio-electronic systems, blocks, nodes, and elements.