Using the mathematical apparatus of the artificial neural networks theory in the development of nonlinear models of field-effect transistors
Based on the mathematical apparatus of the artificial neural networks theory, a nonlinear model of a field-effect transistor has been developed, the distinctive feature of which is a possibility of training neural networks used to approximate the current-voltage characteristic and gate-drain and gate-source capacitances of the nonlinear model of the transistor by optimization algorithms built into popular microwave CAD systems. This makes it possible to use the well-known advantages of neural networks in the function approximation tasks to increase the reliability of the results of nonlinear modeling of microwave devices based on field-effect transistors. This approach can be widely used in the development of libraries of models of active and passive elements for monolithic integrated circuits without using specialized software for training neural networks.