Results 231 to 240 of about 4,125,808 (289)

Unsupervised Learning of Higher-Order Statistics

Neural Processing Letters, 1999
This paper deals with the adaptive extraction of higher-order statistics of related signals. We will show how to use higher-order neural networks to adaptively extract the higher-order cumulant matrices and tensors with an invariant weight norm.
Fa-Long Luo, Rolf Unbehauen, Tertulien Ndjountche   +2 more
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Detecting the MB1 with Higher-Order Statistics

2008 International Conference on Computational Intelligence and Security, 2008
MB1 is a very promising steganography. In this paper, a novel steganalysis scheme is presented to detect MB1. Many experiments are carried out based on high order features, and some useful propositions are learned from those experimental results. Based on those propositions we propose an effective MB1 detection algorithm. Experimental results show that
Donghui Hu, Lina Wang 0001, Xiaqiu Jiang, Tingting Zhu, Yuntao Yue   +4 more
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Low-rank estimation of higher order statistics

IEEE Transactions on Signal Processing, 1997
Low-rank estimators for higher order statistics are considered in this paper. The bias-variance tradeoff is analyzed for low-rank estimators of higher order statistics using a tensor product formulation for the moments and cumulants. In general, the low-rank estimators have a larger bias and smaller variance than the corresponding full-rank estimator ...
Thomas F. Andre, Robert D. Nowak, Barry D. Van Veen   +2 more
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Signal detection by using higher order statistics

1993 IEEE International Symposium on Circuits and Systems, 2002
The performance of a traditional energy-based detector relies finally on signal-to-noise ratio (SNR). To improve the detection performance of the weak non-Gaussian signal embedded in Gaussian noise, both the third order and the second order statistics of the observed data are used to construct a two-channel detector.
Pinxing Lin, Shiyi Mao
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Speech Processing Using Higher Order Statistics

1993 IEEE International Symposium on Circuits and Systems, 2002
The potential use of third-order statistics (TOS) in speech processing applications is examined. A source-system speech representation and analysis algorithm is considered. It computes the autoregressive (AR) parameters of speech from its third-order cumulants.
Ines Jebali Gdoura, Philipos C. Loizou, Andreas Spanias   +2 more
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Almost-Periodic Higher Order Statistic Estimation

IEEE Transactions on Information Theory, 2011
In this paper, stochastic processes with higher order statistical functions decomposable into an almost-periodic function plus a residual term not containing finite-strength additive sinewave components are considered. These processes arise in mobile communications when almost-cyclostationary (ACS) processes pass through time-varying channels.
NAPOLITANO, ANTONIO, TESAURO M.
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Statistical Estimation of Higher-Order Spectra

Theory of Probability & Its Applications, 1986
The problem to construct estimators of higher order spectral densities of stationary random sequences has been discussed by a number of authors. Unfortunately, all proposed statistics fail to be consistent estimators in the whole parameter range. In this paper, the author analyzed statistics free from the mentioned disadvantage. They are constructed by
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Higher-order statistics in object recognition

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2002
A higher-order statistical theory of matching models against images is developed. The basic idea is to take into account how much of an object can be seen in the image, and what parts of it are jointly present. It is shown that this additional information can improve the specificity (i.e., reduce the probability of false positive matches) of a ...
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