Title :
A transiently chaotic neural-network implementation of the CDMA multiuser detector
Author :
Wang, Baoyun ; Nie, Jingnan ; He, Zhenya
Author_Institution :
Dept. of Inf. Eng., Nanjing Univ. of Posts & Telecommun., China
fDate :
9/1/1999 12:00:00 AM
Abstract :
The complex dynamics of the chaotic neural networks makes it possible for them to escape from local minimum of the simple gradient descent neurodynamics. We use a transiently chaotic neural network to detect the CDMA multiuser signals and hence obtain an implementation scheme of the CDMA multiuser detector (TCNN-MD). Computer simulation results show that the proposed detector is clearly superior to Hopfield neural-network-based detector
Keywords :
bifurcation; chaos; code division multiple access; neural nets; signal detection; CDMA multiuser detector; complex dynamics; local minimum; simple gradient descent neurodynamics; transiently chaotic neural-network; Chaos; Chaotic communication; Computer simulation; Degradation; Detectors; Helium; Multiaccess communication; Multiuser detection; Neural networks; Neurodynamics;
Journal_Title :
Neural Networks, IEEE Transactions on