Suchergebnisse - recursive regularisation parameter selection method

Recursive regularisation parameter selection for sparse RLS algorithm von Sun, Dajun, Liu, Lu, Zhang, Youwen

“… In this Letter, the authors propose a recursive regularisation parameter selection method for sparse recursive least squares (RLS) algorithm …”
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Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets von Park, Heewon, Imoto, Seiya, Miyano, Satoru

“… Uncovering driver genes is crucial for understanding heterogeneity in cancer. L1-type regularization approaches have been widely used for uncovering cancer driver genes based on genome-scale data …”
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A multi-frequency iterative imaging method for discontinuous inverse medium problem von Zhang, Lei, Feng, Lixin

“… The selection criteria of regularization parameter is given by the method of generalized cross-validation …”
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A regularised fast recursive algorithm for fraction model identification of nonlinear dynamic systems von Zhang, Li, Li, Kang, Du, Dajun, Li, Yihuan, Fei, Minrui

“… To accurately identify the fraction model is however challenging, and this paper presents a regularised fast recursive algorithm (RFRA …”
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Tree-Structured Clustering in Fixed Effects Models von Berger, Moritz, Tutz, Gerhard

“… ) method is proposed that identifies clusters of units that share the same effect. The approach reduces the number of parameters to be estimated and is useful …”
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Proportionate RLS with l1 norm regularization: Performance analysis and fast implementation von Qin, Zhen, Tao, Jun, Xia, Yili, Yang, Le

“… Existing methods are designed by either incorporating a sparse regularization term, e.g., l1-norm, into the standard RLS cost function or introducing a proportionate matrix into the updating equation …”
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Online sequential echo state network with sparse RLS algorithm for time series prediction von Yang, Cuili, Qiao, Junfei, Ahmad, Zohaib, Nie, Kaizhe, Wang, Lei

“… Thirdly, an adaptive selection mechanism for the ℓ0 or ℓ1 norm regularization parameter is designed …”
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A Variable Regularized Recursive Subspace Model Identification Algorithm With Extended Instrumental Variable and Variable Forgetting Factor von Lin, Jian-Qiang, Chan, Shing-Chow, Tan, Hai-Jun

“… This paper proposes a new smoothly clipped absolute deviation (SCAD) regularized recursive subspace model identification algorithm with square root(SR …”
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Recursive regularization for inferring gene networks from time-course gene expression profiles von Shimamura, Teppei, Imoto, Seiya, Yamaguchi, Rui, Fujita, André, Nagasaki, Masao, Miyano, Satoru

“… This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005 …”
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A new QR decomposition-based RLS algorithm using the split Bregman method for L1-regularized problems von Chu, Y.J., Mak, C.M.

“… This algorithm is derived from the recursive least squares (RLS) optimization problem, where the SB method is used to separate the regularization term from the constrained optimization …”
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Recursive least square–based fast sparse multipath channel estimation von Chen, Yu, Gui, Guan

“… For the stable wireless propagation to be ensured, linear adaptive channel estimation algorithms, eg, recursive least square and least mean square, have been developed …”
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Recursive SURE for iterative reweighted least square algorithms von Xue, Feng, Yagola, Anatoly G., Liu, Jiaqi, Meng, Gang

“… Iterative re-weighted least square (IRLS) algorithms for -minimization problems require to select proper value of regularization parameter, for which Stein's unbiased risk estimate (SURE …”
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A New Transform-Domain Regularized Recursive Least M-Estimate Algorithm for a Robust Linear Estimation von Chan, S C, Zhang, Z G, Chu, Y J

“… regularization parameters are developed for recursive implementation of the TD-R-ME algorithm. Simulation results show that the proposed TD regularized QR recursive least M-estimate (TD-R-QRRLM …”
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A recursive predictive risk estimate for proximal algorithms von Xue, Feng, Du, Runle, Liu, Jiaqi

“… For accurate signal reconstruction, proximal gradient methods generally require proper selection of regularization parameter …”
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Regularization Based Sparse Support Recovery for Asynchronous Multicarrier Modulation Signals in Cognitive Radio Networks von Baral, Ashwin Bhobani, Narngoong, Won, Torlak, Murat

“… ) based regularization method for identifying the active subcarriers of the asynchronous multicarrier modulation signals at the sub-Nyquist sampling rate …”
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Covariance regularization in inverse space von Ueno, Genta, Tsuchiya, Takashi

“… Modelling of the covariance structure consists of the regularization of a sample covariance and the constraint of a dynamic relationship …”
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A novel locally regularized automatic construction method for RBF neural models von Du, Dajun, Li, Xue, Fei, Minrui, Irwin, George W.

“… This is achieved by proposing a locally regularized automatic construction (LRAC) method which combines a recently proposed fast recursive algorithm (FRA …”
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Application of Auto-Regulative Sparse Variational Mode Decomposition in Mechanical Fault Diagnosis von Li, Huipeng, Zhou, Fengxing, Xu, Bo, Yan, Baokang, Zhou, Fengqi

“… The variational mode decomposition (VMD) method has been widely applied in the field of mechanical fault diagnosis as an excellent non-recursive signal processing tool …”
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Recursive Mahalanobis Separability Measure for Gene Subset Selection von Mao, Kezhi Z, Wenyin Tang

“… Mahalanobis class separability measure provides an effective evaluation of the discriminative power of a feature subset, and is widely used in feature selection …”
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Revealing the Non-uniqueness Inherent in MT Inversion: A Comparative Study of Influential Factors and Algorithm-Dependent Uncertainties in FEMTIC and ModEM with USArray MT Data von Song, Han, Usui, Yoshiya, Uyeshima, Makoto, Yu, Peng, Diba, Dieno, Yang, Bo, Baba, Kiyoshi, Koyama, Takao

“… Specifically, we assessed the impact of regularization …”
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