Assuming that noise free auto-correlations or auto-bicorrelations are available to guide optimization, signal can be recovered from a noise background to some extent. A synthetic example is employed to demonstrate the procedure of noise rejection by signal optimization. Except for noise bursts at higher frequencies, the auto-bicorrelation approach gives better results
In this paper, it is shown that the use of a particular autocorrelation estimator, with ¯xed-length ...
Random signals and noise are present in many engineering systems and networks. Signal processing tec...
Abstract- Acoustical noises or background noises degrade the quality and intelligibility of the spee...
Previous research has found autocorrelation domain as an appropriate domain for signal and noise sep...
Time correlation and decorrelation are well established tools to improve the signal to noise ratio o...
One major concern in the design of speech recognition systems is their performance in real environme...
Abstract Autocorrelation domain is a proper domain for clean speech signal and noise separation. In ...
Consider a signal s(t) in presence of an additive noise n(t) and suppose that another noise v(t), st...
We study the multi-target detection problem of recovering a target signal from a noisy measurement t...
When designing noise robust speech recognition feature extraction algorithms, it is common to assume...
,4n investigation is made of the application of the autocorrelation matrix method to the anal-ysis o...
A signal recovery technique is motivated and derived for the recovery of several nonnegative signals...
We introduce an algorithm for nonlinear noise reduction which is based on locally linear fits to the...
Statistical model-based methods are presented for the reconstruction of autocorrelated signals in im...
Pseudo-random signal correlation techniques can irnprove the flaw detection capability of ultrasonic...
In this paper, it is shown that the use of a particular autocorrelation estimator, with ¯xed-length ...
Random signals and noise are present in many engineering systems and networks. Signal processing tec...
Abstract- Acoustical noises or background noises degrade the quality and intelligibility of the spee...
Previous research has found autocorrelation domain as an appropriate domain for signal and noise sep...
Time correlation and decorrelation are well established tools to improve the signal to noise ratio o...
One major concern in the design of speech recognition systems is their performance in real environme...
Abstract Autocorrelation domain is a proper domain for clean speech signal and noise separation. In ...
Consider a signal s(t) in presence of an additive noise n(t) and suppose that another noise v(t), st...
We study the multi-target detection problem of recovering a target signal from a noisy measurement t...
When designing noise robust speech recognition feature extraction algorithms, it is common to assume...
,4n investigation is made of the application of the autocorrelation matrix method to the anal-ysis o...
A signal recovery technique is motivated and derived for the recovery of several nonnegative signals...
We introduce an algorithm for nonlinear noise reduction which is based on locally linear fits to the...
Statistical model-based methods are presented for the reconstruction of autocorrelated signals in im...
Pseudo-random signal correlation techniques can irnprove the flaw detection capability of ultrasonic...
In this paper, it is shown that the use of a particular autocorrelation estimator, with ¯xed-length ...
Random signals and noise are present in many engineering systems and networks. Signal processing tec...
Abstract- Acoustical noises or background noises degrade the quality and intelligibility of the spee...