Results 231 to 240 of about 137,583 (290)

Moving Sum Procedure for Multiple Change Point Detection in Large Factor Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper proposes a moving sum methodology for detecting multiple change points in high‐dimensional time series under a factor model, where changes are attributed to those in loadings as well as emergence or disappearance of factors. We establish the asymptotic null distribution of the proposed test for family‐wise error control and show the
Matteo Barigozzi, Haeran Cho, Lorenzo Trapani   +2 more
wiley   +1 more source

A Novel VSS-LMS Algorithm Based on Modified Versoria Function for Anti-Jamming. [PDF]

Sensors (Basel)
Tian B, Feng Y, Liu F, Song B, Guo S.
europepmc   +1 more source

Performance of Hammerstein Spline Adaptive Filtering Based on Fair Cost Function for Denoising Electrocardiogram Signals. [PDF]

Biomimetics (Basel)
Sitjongsataporn S, Wiangtong T.
europepmc   +1 more source

Development and validation of an interpretable Random Forest model for predicting recurrence after endoscopic submucosal dissection in superficial oesophageal squamous cell carcinoma. [PDF]

Ann Med
Zhu Z, Li Q, Chen W, Sun P, Li X, Yang Y, Li S, Zhu G, Zhu H.   +8 more
europepmc   +1 more source

An Improved Extensive Cancellation Method for Clutter Removal in Passive Bistatic Radar. [PDF]

Sensors (Basel)
Chen G, Su S, Zhang D, Wang S, Ping Y, Li F.   +5 more
europepmc   +1 more source

Signal Detection Based on Separable CNN for OTFS Communication Systems. [PDF]

Entropy (Basel)
Wang Y, Zhang Z, Li H, Zhou T, Cheng Z.
europepmc   +1 more source

Quantitative method of pipeline magnetic leakage internal signal detection on the basis of an improved neural network. [PDF]

Sci Rep
Wang G, Bei S, Zuo Y, Zhang H.
europepmc   +1 more source

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Variable Regularized Square Root Recursive Least Square Method

IFAC Proceedings Volumes, 2012
In this paper, we develop the variable regularized square root recursive least square method which is in order to track time-varying parameters extended by an exponential forgetting factor (EF-VR-SRRLS). The proposed approach is arisen from the exact recursification of the original batch mode method solving the restricted quadratic problem.
Jakub Dokoupil, Vladimír Burlak
openaire   +1 more source

Recursive unsupervised fully constrained least squares methods

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Linear spectral mixture analysis (LSMA) generally performs with signatures assumed to be known to form a linear mixing model to be known. Unfortunately, this is generally not the case in real world applications. An unsupervised fully constrained least squares (UFCLS) method has been proposed to find these desired signatures.
null ShihYu Chen, null Yen-Chieh Ouyang, null Chein-I Chang   +2 more
openaire   +1 more source