A Neural Network-Based Design Automation of a Second Generation Current Conveyor

Author

Kahraman, Nihan ; Kiyan, T.

Author_Institution

Electron. & Telecommun. Eng., Yildiz Tech. Univ. Istanbul, Istanbul, Turkey

Volume

2

fYear

2014

fDate

10-13 March 2014

Firstpage

313

Lastpage

314

Abstract

An artificial neural network approach for the automated design of a positive type second generation current conveyor is presented in this paper. A multi-layer perceptron structure is successfully employed to estimate the corresponding transistor dimensions for a given set of desired performance criteria of the circuit. Data generated by a circuit simulation program (SPICE) is used to train the artificial neural network. The excellent agreement between the desired specifications and the actual results from SPICE simulation results approves that neural networks are powerful tools for automated analog circuit sizing.

Keywords

SPICE; analogue circuits; circuit simulation; current conveyors; electronic design automation; multilayer perceptrons; performance evaluation; transistor circuits; SPICE simulation; artificial neural network approach; automated analog circuit sizing; circuit performance criteria; circuit simulation program; multilayer perceptron structure; neural network-based design automation; positive type second generation current conveyor; transistor dimensions; Artificial neural networks; Bandwidth; Design automation; Optimization; SPICE; Simulation; Transistors; Computer aided design (CAD); multilayer perceptron (MLP); neural networks; positive second generation current conveyor (CCII+);

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Computational Intelligence (CSCI), 2014 International Conference on

Conference_Location

Las Vegas, NV

Type

conf

DOI

10.1109/CSCI.2014.150

Filename

6822361