This work presents the introduction of a neural network-based optimization approach in the tuning of voltage-controlled circuits (such as active filters). A custom calibration system has been already presented by the same Authors. It was realized with a hardware interface and a dedicated software based on a modified version of a Differential Evolution algorithm. In this paper the implemented algorithms are described in detail together with a possible integration of the neural network synthesis to further enhance performance of the proposed system. As the first step in exploiting neural networks, in this paper they are used as a tool for speeding up the choice of initial values of the filter control voltages. Neural networks are used to replace a look-up table representing the relationship between filter parameters, the central frequency and the corresponding attenuation, and the control voltages. According to the obtained results, in such a way, the optimization time is shortened significantly.

On the Introduction of Neural Network-based Optimization Algorithm in an Automated Calibration System

Leoni A.;Pantoli L.
2019

Abstract

This work presents the introduction of a neural network-based optimization approach in the tuning of voltage-controlled circuits (such as active filters). A custom calibration system has been already presented by the same Authors. It was realized with a hardware interface and a dedicated software based on a modified version of a Differential Evolution algorithm. In this paper the implemented algorithms are described in detail together with a possible integration of the neural network synthesis to further enhance performance of the proposed system. As the first step in exploiting neural networks, in this paper they are used as a tool for speeding up the choice of initial values of the filter control voltages. Neural networks are used to replace a look-up table representing the relationship between filter parameters, the central frequency and the corresponding attenuation, and the control voltages. According to the obtained results, in such a way, the optimization time is shortened significantly.
978-1-7281-0878-0
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/150417
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact