DocumentCode :
285063
Title :
A neural network for estimating the parameters of multiple sinusoids
Author :
Karras, D.A. ; Varoufakis, S.J.
Author_Institution :
Inst. of Inf. & Telecommun., Athens, Greece
Volume :
2
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
1005
Abstract :
The authors present an approach, using a circuit based on the concept of neural networks, for estimating the parameters of multiple sinusoids. The computation of the parameters in the case of analog circuit realization is extremely fast because the network´s speed is limited only by the time constants of the operational amplifiers. Several examples are used to test the efficiency of the method by simulation. This is done for the noiseless case as well as for the case where noise is present. The proposed artificial neural network (ANN) exhibits good performance for near continuous frequencies and for the case where only a small part of the signal is covered by the sampling points
Keywords :
neural nets; parameter estimation; signal processing; efficiency; multiple sinusoids; neural network; parameter estimation; sampling points; signal processing; Analog circuits; Analog computers; Artificial neural networks; Circuit noise; Circuit testing; Computational modeling; Computer networks; Neural networks; Operational amplifiers; Parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.226856
Filename :
226856
Link To Document :
بازگشت