DocumentCode :
2537925
Title :
Noise-Canceller based on Generalized Neural Network
Author :
Mishra, Agya ; Yadav, R.N. ; Trivedi, D.K.
Author_Institution :
Maulana Azad Nat. Inst. of Technol., Bhopal
Volume :
3
fYear :
2007
fDate :
12-14 Feb. 2007
Firstpage :
1998
Lastpage :
2000
Abstract :
The noise cancellation has become the essential requirement in the field of signal processing. This paper presents the noise-cancellation technique based on higher-order neural network (HONN). These networks consists of an aggregation function, generalized neural network (GNN) which is based on the generalized-mean of all the inputs applied to it. The results of GNN is also compared with the existing recursive least square algorithm (RLS) of adaptive filtering. The simulation results show these network can be suitably applied for the signal detection.
Keywords :
adaptive filters; least squares approximations; neural nets; recursive estimation; signal denoising; signal detection; adaptive filtering; aggregation function; generalized neural network; higher-order neural network; noise cancellation; recursive least square algorithm; signal detection; signal processing; Adaptive filters; Neural networks; Neurons; Noise cancellation; Noise figure; Noise generators; Resonance light scattering; Signal detection; Signal processing; Signal processing algorithms; Generalized mean neuron; Noise canceller; Noisy signals; function approximation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Communication Technology, The 9th International Conference on
Conference_Location :
Gangwon-Do
ISSN :
1738-9445
Print_ISBN :
978-89-5519-131-8
Type :
conf
DOI :
10.1109/ICACT.2007.358764
Filename :
4195566
Link To Document :
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