Open AccessSimulation of Noise-Cancelling in the Cockpit of an Aircraft Using Two-Rate Hybrid Neural Network
Author(s) -
Igor Astrov,
Svetlana Tatarly
Publication year - 2007
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2007.02002
Subject(s) - cockpit , artificial neural network , computer science , noise (video) , aircraft noise , active noise control , simulation , acoustics , artificial intelligence , engineering , aeronautics , noise reduction , physics , image (mathematics)
This paper presents the two-rate hybrid neural network (TRHNN) for processing of noisy signal. The received TRHNN consists of "fast" ADAptive LInear NEuron neural network (FADALINENN) and "slow" radial basis neural network (SRBNN). The illustrative design example - noise-cancelling of noisy pilot's voice pattern - was carried out using the TRHNN. The received TRHNN has high speed of signal processing. This example demonstrates that the proposed TRHNN is capable not only to recognize the pilot's voice in the noisy voice pattern, but also to restore the pilot's voice. The simulation results with use the software package Simulink show the computing procedure and applicability of the TRHNNs for fast-acting signal processing and analysis in real-time flight conditions