Synchronization using an adaptive threshold in a biologically inspired spatiotemporal neuron

Author

Richardson, Warren A. ; Clouse, Raja L. ; Kim, Soowon ; Waldron, Manjula B.

Author_Institution

Biomed. Eng. Center, Ohio State Univ., Columbus, OH, USA

Volume

2

fYear

1996

fDate

3-6 Jun 1996

Firstpage

728

Abstract

It is shown that an adaptive threshold can be used to perform synchronization in a network of biologically inspired neurons. The proposed learning algorithm is able to synchronize a network of neurons with similar inputs arranged in a grid-like architecture with nearest neighbor connections. This synchronization was performed on networks of varying sizes (2×1 and 32×32). This approach may be useful in applications of spatiotemporal signal processing, such as image segregation and temporal feature binding

Keywords

learning (artificial intelligence); neural nets; signal processing; synchronisation; adaptive threshold; biologically inspired spatiotemporal neuron; grid-like architecture; image segregation; learning algorithm; nearest neighbor connections; spatiotemporal signal processing; synchronization; temporal feature binding; Artificial neural networks; Attenuation; Biological system modeling; Biomedical engineering; Delay effects; Frequency synchronization; Neurons; Oscillators; Signal processing algorithms; Spatiotemporal phenomena;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1996., IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-7803-3210-5

Type

conf

DOI

10.1109/ICNN.1996.548986

Filename

548986