Analysis to detecting methods of analogue based on variable threshold value neuron

Author

Tang, Jian ; Sun, Bo

Author_Institution

Inst. of Special Equip., Shenyang Ligong Univ., Shenyang, China

fYear

2009

fDate

5-7 Aug. 2009

Firstpage

1356

Lastpage

1359

Abstract

In this paper, piecewise linearization and piecewise variable slope are used to train the detecting methods of non-linear analogue based on variable threshold neuron. The relationship between two training methods is given. The training method of piecewise variable slope can calibrate the detecting curve from the training method of piecewise linearization at the sampled-data feature, which improves the detecting precision and detecting resolution. The simulation result above-mentioned are provided.

Keywords

distributed control; learning (artificial intelligence); linearisation techniques; nonlinear control systems; piecewise linear techniques; sampled data systems; signal detection; distributed control system; nonlinear analogue detection method; piecewise linearization; piecewise variable slope; sampled-data feature; training method; variable threshold value neuron; Artificial intelligence; Artificial neural networks; Automation; Embedded system; Information science; Logistics; Neurons; Production; Sun; Testing; artificial neuron; distributed system; embedded system; non-linear analogue detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2009. ICAL '09. IEEE International Conference on

Conference_Location

Shenyang

Print_ISBN

978-1-4244-4794-7

Electronic_ISBN

978-1-4244-4795-4

Type

conf

DOI

10.1109/ICAL.2009.5262746

Filename

5262746