Improved noise reduction in audio signals using spectral resolution enhancement with time-domain signal extrapolation

2005 ◽  
Vol 13 (6) ◽  
pp. 1210-1216 ◽  
Author(s):  
I. Kauppinen ◽  
K. Roth
Keyword(s):  
Noise Reduction ◽  
Spectral Resolution ◽  
Time Domain ◽  
Resolution Enhancement ◽  
Audio Signals ◽  
Time Domain Signal ◽  
Signal Extrapolation

HILBERT SPECTRUM IN TIME-FREQUENCY REPRESENTATION OF AUDIO SIGNALS CONSIDERING DISJOINT ORTHOGONALITY

2010 ◽  
Vol 02 (03) ◽  
pp. 313-336 ◽  
Author(s):  
MD. KHADEMUL ISLAM MOLLA ◽  
KEIKICHI HIROSE
Keyword(s):  
Hilbert Transform ◽  
Time Domain ◽  
Adaptive Method ◽  
Intrinsic Mode Functions ◽  
Audio Signals ◽  
Hilbert Spectrum ◽  
Time Frequency ◽  
Time Domain Signal ◽  
Frequency Representation ◽  
Non Stationary Signal

The performance of Hilbert spectrum (HS) in time-frequency representation (TFR) of audio signals is investigated in this paper. HS offers a fine-resolution TFR of time domain signals. It is derived by applying empirical mode decomposition (EMD), a newly developed data adaptive method for nonlinear and non-stationary signal analysis together with Hilbert transform. EMD represents any time domain signal as a sum of a finite number of bases called intrinsic mode functions (IMFs). The instantaneous frequency responses of the IMFs derived through Hilbert transform are arranged to obtain the TFR of the analyzing signal yielding the HS. The disjoint orthogonal property of audio signals is used as the decisive factor to measure the efficiency in TFR. Several audio signals are considered as disjoint orthogonal if not more than one source is active at any time-frequency cell. The performance of HS is compared with well known and widely used short-time Fourier transform technique for TFR. The experimental results show that HS based method performs better in time-frequency representation of the audio signals with the consideration of disjoint orthogonality.

Segmented noise reduction based on Brillouin-spectrum-partition in Brillouin optical time domain sensors

2021 ◽  
pp. 1-1
Author(s):  
Yuyang Zhang ◽  
Yuangang Lu ◽  
Liang Chen ◽  
Tong Wu ◽  
Chongjun He
Keyword(s):  
Noise Reduction ◽  
Time Domain ◽  
Optical Time ◽  
Brillouin Spectrum

scholarly journals Is the time domain signal-averaged electrocardiogram helpful in patients with ventricular tachycardia without apparent structural heart disease?

1995 ◽  
Vol 18 (10) ◽  
pp. 568-572 ◽  
Author(s):  
Yelena S. K. Orlov ◽  
Michael A. Brodsky ◽  
Michael V. Orlov ◽  
Byron J. Allen ◽  
Rex J. Winters
Keyword(s):  
Heart Disease ◽  
Ventricular Tachycardia ◽  
Time Domain ◽  
Structural Heart Disease ◽  
Time Domain Signal ◽  
The Time Domain

scholarly journals NMR Resolution Enhancement and Homonuclear Decoupling Using Non-Uniform Weighted Sampling

2020 ◽  
Author(s):  
Chris Waudby ◽  
John Christodoulou
Keyword(s):  
Linear Prediction ◽  
Resolution Enhancement ◽  
Simple Method ◽  
Uniform Sampling ◽  
Homonuclear Decoupling ◽  
Time Domain Signal ◽  
Window Functions ◽  
Uniform Noise ◽  
Increased Sensitivity ◽  
The Time Domain

Non-uniform weighted sampling (NUWS) is a simple method for multi-dimensional NMR spectroscopy in which window functions are applied during acquisition by sampling varying numbers of scans across indirect dimensions. While NUWS was previously shown to provide modest increases in sensitivity, here we describe a complementary application to enhance spectral resolution by increasing the sampling of later points of the time domain signal. Moreover, by combining NUWS with carefully constructed apodization functions signal envelopes can be modulated in an arbitrary manner while retaining a uniform noise level, permitting further signal manipulations such as linear prediction and non-uniform sampling (NUS). We leverage this to develop a combined NUWS-NUS scheme for broadband homonuclear decoupling, with substantially increased sensitivity in comparison to constant time experiments.

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