Identification of the specification parameters for a voltage controlled oscillator using an artificial neural network with a genetic algorithm

This paper presents the application of an artificial neural network with a genetic algorithm for identifying the selected specification parameters of a voltage-controlled oscillator (VCO). In modern electronics, the complexity of the production process may cause errors in analogue and mixed-signal electronic circuits, and inaccuracies in this technological process have a direct impact on the specification parameters of a VCO. The modern market requires that the production process has to be as quick as possible, and therefore testing systems should be fast and have the highest efficiency of parameter identification. In the following paper, a genetic algorithm is used to optimise the number of output signal measurement points, which allows them to be identified by the specification parameters of the VCO that are selected by an artificial neural network. The proposed method is characterised by shortening the test time of the system while maintaining a high efficiency in the identification of the selected design specification parameters.