Results 221 to 230 of about 20,110 (263)

Adaptive estimation with soft thresholding penalties

Statistica Neerlandica, 2002
We show that various robust nonparametric regression estimators, such as the least absolute deviations estimator, can be made adaptive (up to logarithmic factors), by adding a soft thresholding type penalty to the loss function. As an example, we consider the situation where the roughness of the regression function is described by a single parameter p.
Loubes, Jean-Michel, van de Geer, Sara
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Variable threshold soft decision decoding

Electronics and Communications in Japan (Part III: Fundamental Electronic Science), 1989
AbstractSoft decision decoding is a decoding method which tries to improve the error‐correcting capability by utilizing the information concerning the reliability of the received symbol. One of the soft decision decoding methods for practically useful block code, is APP (a posteriori probability) decoding applicable to the majority‐logic de‐codable ...
Kazuhiko Yamaguchi, Hiroshi Iizuka, Eiji Nomura, Hideki Imai   +3 more
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Least Soft-Threshold Squares Tracking

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
In this paper, we propose a generative tracking method based on a novel robust linear regression algorithm. In contrast to existing methods, the proposed Least Soft-thresold Squares (LSS) algorithm models the error term with the Gaussian-Laplacian distribution, which can be solved efficiently.
Dong Wang, Huchuan Lu, Ming-Hsuan Yang
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Soft thresholding by noise invalidation

2008 24th Biennial Symposium on Communications, 2008
A new thresholding technique for data denoising is proposed. Using statistical properties of additive noise, this method provides an adaptive data dependent soft threshold to remove the effects of noise. The observed data can be denoised in any orthogonal basis.
Soosan Beheshti, Nima Nikvand, Xavier N. Fernando   +2 more
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Dynamical Threshold of Diluteness of Soft Colloids

ACS Macro Letters, 2014
Soft colloids are hybrids between linear polymers and hard colloids. Their solutions exhibit rich phase phenomenon due to their unique microstructure. In scaling theories, a geometrically defined overlap concentration c* is used to identify the concentration regimes of their solutions characterized with distinct conformational properties.
Xin, Li, Luis E, Sánchez-Diáz, Bin, Wu, William A, Hamilton, Péter, Falus, Lionel, Porcar, Yun, Liu, Changwoo, Do, Antonio, Faraone, Gregory S, Smith, Takeshi, Egami, Wei-Ren, Chen   +11 more
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Threshold Decomposition of Gray-Scale Soft Morphology into Binary Soft Morphology

Graphical Models and Image Processing, 1995
Gray-scale soft mathematical morphology is the natural extension of binary soft mathematical morphology which has been shown to be less sensitive to additive noise and to small variations. But gray-scale soft morphological operations are difficult to implement in real time.
Pu, Christopher C., Shih, Frank Y.
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De-noising by soft-thresholding

IEEE Transactions on Information Theory, 1995
Summary: The author and \textit{I. M. Johnstone} [Biometrika 81, No. 3, 425--455 (1994; Zbl 0815.62019)] proposed a method for reconstructing an unknown function \(f\) on \([0,1]\) from noisy data \(d_ i = f(t_ i) + \sigma z_ i\), \(i = 0, \dots, n-1\), \(t_ i = i/n\), where the \(z_ i\) are independent and identically distributed standard Gaussian ...
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Threshold decomposition of soft morphological filters

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2002
The properties of soft morphological operations and the new definitions of binary soft morphological operations are presented. It is shown that soft morphological filtering on an arbitrary signal is equivalent to decomposing the signal into binary signals, filtering each binary signal with a binary soft morphological filter, and then reversing the ...
F.Y. Shih, C.C. Pu
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Spectral fuzzy sets and soft thresholding

Information Sciences, 1992
A new concept of spectral fuzzy sets has been introduced for dealing with the uncertainty in subjective assignment of membership value to the elements of a fuzzy set. The concept is characterized by a set of membership functions reflecting an individual's (or several individuals') opinion. The uncertainty due to spectralness has been explained.
Pal, Sankar K., Dasgupta, Ambarish
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Nonlinear multiwavelet transform based soft thresholding

IEEE APCCAS 2000. 2000 IEEE Asia-Pacific Conference on Circuits and Systems. Electronic Communication Systems. (Cat. No.00EX394), 2002
In this paper, as an extension of the wavelet transform, a nonlinear multiwavelet transform is introduced. The advantage of this approach is that the high frequency components of the filtered signal can be enhanced properly by adjusting a parameter that is used to control the nonlinear properties of the multiwavelet transform.
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