Imperial College London

ProfessorDaniloMandic

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Signal Processing
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Krcmar:2000:10.1109/NEUREL.2000.902379,
author = {Krcmar, IR and Bozic, MM and Mandic, DP},
doi = {10.1109/NEUREL.2000.902379},
pages = {33--36},
title = {Global asymptotic stability for RNNs with a bipolar activation function},
url = {http://dx.doi.org/10.1109/NEUREL.2000.902379},
year = {2000}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - © 2000 IEEE. Conditions for global asymptotic stability of a nonlinear relaxation process realized by a recurrent neural network with a hyperbolic tangent activation function are provided. This analysis is based upon the contraction mapping theorem and corresponding fixed point iteration. The derived results find their application in the wide area of neural networks for optimization and signal processing.
AU - Krcmar,IR
AU - Bozic,MM
AU - Mandic,DP
DO - 10.1109/NEUREL.2000.902379
EP - 36
PY - 2000///
SP - 33
TI - Global asymptotic stability for RNNs with a bipolar activation function
UR - http://dx.doi.org/10.1109/NEUREL.2000.902379
ER -