Cyclic Coding and Discrete Wavelet Transform Based Audio Signal Processing

2018 ◽  
Author(s):  
Dogan Yildiz ◽  
Serap Karagol
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Audio Signal ◽  
Discrete Wavelet ◽  
Audio Signal Processing

AUDIO WATERMARKING WITH ANGLE QUANTIZATION BASED ON DISCRETE WAVELET TRANSFORM AND SINGULAR VALUE DECOMPOSITION

2018 ◽  
Vol 6 (2) ◽  
pp. 41-52
Author(s):  
Divya Chadar ◽  
Shailja Shukla
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Auditory System ◽  
Audio Signal ◽  
Singular Value ◽  
New Method ◽  
Discrete Wavelet ◽  
Audio Watermark ◽  
Value Decomposition

An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same. 

Experimental Study of Mine AE Signal Based on Wavelet Analysis

2011 ◽  
Vol 148-149 ◽  
pp. 1127-1130 ◽  
Author(s):  
Xiu Zhi Cheng ◽  
Zhen Yu ◽  
Guang Zhu
Keyword(s):  
Experimental Study ◽  
Signal Processing ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Frequency Domain ◽  
Activity Patterns ◽  
Audio Signal ◽  
P Wave ◽  
Audio Signal Processing ◽  
Ae Signal

Because the wavelet transform can characterize the local signals in time and frequency domain, in the coal mine’s sound signals’ process, an audio signal processing based on wavelet analysis is proposed, the audio signal P wave is isolated and determined by wavelet transform, at the same time, the earthquake source can be located. Through the research of the mine AE signal’s activity patterns, the sound monitoring technology to forecast the mine power disaster is achieved.

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