Title :
A 1.5 V VLSI circuit for the co-channel signal separation
Author :
Ndjountche, Tertulien ; Unbehauen, Rolf ; Luo, Fa-Long
Author_Institution :
Lehrstuhl fur Allgemeine und Theor. Elektrotech., Erlangen-Nurnberg Univ., Germany
Abstract :
In analog implementations of adaptive algorithms, limited voltage ranges and inevitable DC offset voltages that arise in the learning circuit seriously degrade the convergence performance. Using the circuit structures proposed in the paper, these problems are eliminated and the learning characteristic of the resulting network is improved. The test results are obtained from a structure with two channels using a stochastic gradient algorithm in order to minimize the cost function defined as the output signal cross-correlation. This algorithm allows the identification of the channels and the reconstruction of the signals so long as the signals are L2 integrable
Keywords :
VLSI; analogue circuits; neural nets; VLSI circuit; adaptive algorithms; analog VLSI circuit; analog implementations; channel deconvolution; co-channel signal separation; learning circuit; second-order statistic algorithm; signal separation; stochastic gradient algorithm; Adaptive algorithm; Circuit testing; Convergence; Cost function; Degradation; Signal processing; Source separation; Stochastic processes; Very large scale integration; Voltage;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.860773