Results 211 to 220 of about 195,242 (267)

Adaptive CFAR detection of multidimensional signals

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
Adaptive detection of multidimensional signals in the presence of interference with unknown covariance matrix is an expanding topic in a variety of scenarios ranging from radar/sonar to digital communication systems. We attack the problem of detecting a multidimensional radar signal, modeled as an unknown N/spl times/H matrix, embedded in Gaussian ...
E. Conte, A. De Maio, C. Galdi, RICCI, Giuseppe   +3 more
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Adaptive robust signal detection algorithms

Proceedings, 6th International Conference on Actual Problems of Electronic Instrument Engineering, 2003
The adaptive, asymptotically robust algorithms developed permit signal detection in independent noise of arbitrary form. The algorithms demonstrate high efficiency in the cases of heavy tail distribution, where conventional algorithms are usually characterized by low noise immunity.
V.A. Bogdanovich, A.Ya. Groshev
openaire   +1 more source

Adaptive detection of transient signals

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1986
The paper discusses the problem of detecting transient signals of unknown waveforms in white Gaussian noise. The signals are modeled as impulse responses of rational transfer functions with unknown parameters. A generalized likelihood ratio test (GLRT) is proposed and its statistical properties are analyzed.
B. Porat, B. Friedlander
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Parametric Adaptive Signal Detection for Hyperspectral Imaging

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
Hyperspectral imaging (HSI) sensors can provide very fine spectral resolution that allows remote identification of ground objects smaller than a full pixel in an HSI image. Traditional approaches to the so-called subpixel target signal detection problem are training inefficient due to the need for an estimate of a large-size covariance matrix of the ...
null Hongbin Li, J.H. Michels
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CFAR adaptive detection of distributed signals

Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004., 2005
We consider the problem of detecting distributed signals described by the second order Gaussian models in the presence of noise whose covariance structure and level are both unknown. Such a detection problem is often called the "Gauss-Gauss" problem in that both the signal and the noise are assumed to have Gaussian distributions.
null Yuanwei Jin, B. Friedlander
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Bootstrap methods for adaptive signal detection

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002
A general bootstrap procedure for signal detection is presented. Two methods under this general procedure are given. One method requires a regression model to be available to generate the bootstrap data while the other method assumes a pivot. Examples of detecting known signals, signals with unknown parameters and random signals are given.
null Hwa-Tung Ong, A.M. Zoubir
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Signal detection by adaptive filters

IEEE Transactions on Information Theory, 1961
In den letzten Jahren wurden Empfangssysteme entwickelt, die in der Lage sind, ihre Arbeitsparameter oder ihre Struktur innerhalb bestimmter Grenzen selbsttätig an die Eigenschaften der Empfangssignale anzupassen. Es wird ein solches selbstadaptierendes Filter beschrieben, welches seine Eigenschaften automatisch an impulsförmige Signale anpaßt, die ...
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ASIDT: Adaptive Signal Detection Testing

Perception, 1997
Two-alternative forced choice (2AFC) methods which are routinely used in psychophysics provide criterion-free sensitivity measures but at a high price: 2AFC procedures generally need 2 – 3 times the number of trials than a simple yes/no design to achieve the same level of threshold variability.
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Adaptive RBF neural network in signal detection

Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 2002
This paper addresses the application of locally optimum (LO) signal detection techniques to environments in which the noise density is not known a-priori. For small signal levels, the LO detection rule is shown to involve a nonlinearity which depends on the noise density.
W. Ahmed, D.M. Hummels, M.T. Musavi
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Adaptive detection of distorted digital signals

Radio and Electronic Engineer, 1970
The paper describes a novel approach to the adaptive equalization of a channel, leading to an adaptive detector which promises to achieve in some applications a better performance over a slowly time-varying channel, for a given degree of equipment complexity, than is possible with the more conventional transversal-filter adaptive equalizer.The ...
openaire   +1 more source