JOURNAL ARTICLE

On the multi-channel noise cancellation using beamforming algorithm

Abstract

This paper presents performance analysis of beamforming algorithm for canceling multiple channel noise depending on variation of hidden layer of the multilayer feedforward network and the number of epoch (also known as number of iteration). We consider the learning rate variation of the multi layer perception (MLP) to determine the adaptive learning rate of the network. An MLP has been considered to perform beam-forming, which is an array of sensors connected to the MLP inputs. We use the backpropagation algorithm as the learning rule for MLP and improving the signal quality. This involves a desired signal whilst removing any noise or interference signals which may come from different sources.

Keywords:
Computer science Backpropagation Feed forward Beamforming Algorithm Noise (video) Active noise control Adaptive beamformer Interference (communication) Channel (broadcasting) SIGNAL (programming language) Artificial neural network Speech recognition Artificial intelligence Telecommunications Engineering

Metrics

1
Cited By
0.35
FWCI (Field Weighted Citation Impact)
8
Refs
0.64
Citation Normalized Percentile
Is in top 1%
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Topics

Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Direction-of-Arrival Estimation Techniques
Physical Sciences →  Computer Science →  Signal Processing

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