scholarly journals A Fast Adaptive Speech Extraction Method using Blind Source Separation for Audio Signal Processing

2020 ◽  
Vol 9 (4) ◽  
pp. 727-733
Keyword(s):  
Signal Processing ◽  
Extraction Method ◽  
Statistical Approach ◽  
Audio Signal ◽  
Noise Removal ◽  
Adaptive Signal Processing ◽  
Audio Signal Processing ◽  
Time Frequency ◽  
Signal Processing Methods ◽  
Adaptive Signal

The adaptive signal processing methods are used in several applications like channel estimation, Noise removal and extraction of signals also. The methods vary on time, frequency and statistical approach. In this paper, the source speech signals are separated using different methods like FastICA,PCA and kICA. Comparison of original signal and estimated signals are evaluated for different methods. The implementation was done in MATLAB. The spectrogram, Negentropy and Kurtosis waveforms are plotted for different methods.

Toward an Intelligent Editor of Digital Audio: Signal Processing Methods

1982 ◽  
Vol 6 (1) ◽  
pp. 42 ◽  
Author(s):  
Scott Foster ◽  
W. Andrew Schloss ◽  
A. Joseph Rockmore
Keyword(s):  
Signal Processing ◽  
Audio Signal ◽  
Digital Audio ◽  
Audio Signal Processing ◽  
Processing Methods ◽  
Signal Processing Methods

Design of Adaptive Filter for Health Monitoring on a Gearbox

2006 ◽  
Vol 321-323 ◽  
pp. 1237-1240
Author(s):  
Sang Kwon Lee ◽  
Jung Soo Lee
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Adaptive Filter ◽  
Health Monitoring ◽  
Background Noise ◽  
Adaptive Signal Processing ◽  
Vibration Signals ◽  
Time Frequency ◽  
Frequency Representation ◽  
Adaptive Signal

Impulsive vibration signals in gearbox are often associated with faults, which lead to due to irregular impacting. Thus these impulsive vibration signals can be used as indicators of machinery faults. However it is often difficult to make objective measurement of impulsive signals because of background noise signals. In order to ease the measurement of impulsive signal embedded in background noise, we enhance the impulsive signals using adaptive signal processing and then analyze them in time and frequency domain by using time-frequency representation. This technique is applied to the diagnosis of faults within laboratory gearbox.

Fault Identification for Rotating Machinery Using Adaptive Signal Processing and Time-Frequency Analysis

1997 ◽  
Author(s):  
Sang-Kwon Lee ◽  
Paul R. White
Keyword(s):  
Signal Processing ◽  
Background Noise ◽  
Combustion Engine ◽  
Adaptive Signal Processing ◽  
Rotating Machinery ◽  
Fault Identification ◽  
Vibration Signals ◽  
Time Frequency ◽  
Frequency Representation ◽  
Adaptive Signal

Abstract Impulsive sound and vibration signals in rotating machinery are often associated with faults which lead to due to irregular impacting. Thus these impulsive sound and vibration signals can be used as indicators of machinery faults. However it is often difficult to make objective measurement of impulsive signals because of background noise signals. In order to ease the measurement of impulsive sounds embedded in background noise, we enhance the impulsive signals using adaptive signal processing and then analyze them in time and frequency domain by using time-frequency representation. This technique is applied to the diagnosis of faults within internal combustion engine and industrial gear.

Speech and Audio Signal Applications

2002 ◽  
pp. 200-224
Author(s):  
Hector Perez-Meana ◽  
Mariko Nakano-Miyatake ◽  
Luis Nino-de-Rivera-y-Oyarzabal
Keyword(s):  
Signal Processing ◽  
Adaptive Filters ◽  
Audio Signal ◽  
Adaptive Signal Processing ◽  
Basic Principles ◽  
Signal Processing Systems ◽  
Adaptive Signal

This chapter reviews the basic principles of multirate adaptive filters together with some of their most successful applications, as well as some recently proposed schemes that improve the subband adaptive signal processing systems.

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