A detecting method of analog signals based on variable threshold value neuron

Author

Sun, Bo ; Lin, Jingfu ; Chen, Yong

Author_Institution

Fac. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

1925

Lastpage

1928

Abstract

The paper puts forward a variable threshold value artificial neuron structure. The neural function between the output and input can be accurately trained by increasing the density of threshold value. Combined with characteristic of distributed control systems, a long-distance intelligent marking method is proposed and is applied to carry out the process of training threshold value and weight coefficient. The method is prone to detect analog signals fast and precise. A timing duplicate marking method is presented to ensure the reliability of data transfer. The simulation of the model is carried out, simulation results of nonlinear function are provided.

Keywords

distributed control; neurocontrollers; nonlinear control systems; signal detection; analog signal detecting method; artificial neuron structure; data transfer reliability; distributed control system; long-distance intelligent marking method; nonlinear function; threshold value training; timing duplicate marking method; variable threshold value; Artificial intelligence; Artificial neural networks; Circuits; Distributed control; Electric variables measurement; Hardware; Information science; Intelligent systems; Neurons; Timing; artificial neuron structure; distributed control system; long-distance intelligent marking method; threshold value; timing duplicate marking method;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636474

Filename

4636474