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Highly Accurate Golden Section Search Algorithms and Fictitious Time Integration Method for Solving Nonlinear Eigenvalue Problems
《Computer Modeling in Engineering & Sciences》2024年第5期1317-1335,共19页Chein-Shan Liu Jian-Hung Shen Chung-Lun Kuo Yung-Wei Chen 
the National Science and Tech-nology Council,Taiwan for their financial support(Grant Number NSTC 111-2221-E-019-048).
This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solve...
关键词：Nonlinear eigenvalue problem quadratic eigenvalue problem two new merit functions golden section search algorithm fictitious time integration method 
A Highly Accurate Dysphonia Detection System Using Linear Discriminant Analysis
《Computer Systems Science & Engineering》2023年第3期1921-1938,共18页Anas Basalamah Mahedi Hasan Shovan Bhowmik Shaikh Akib Shahriyar 
The recognition of pathological voice is considered a difficult task for speech analysis.Moreover,otolaryngologists needed to rely on oral communication with patients to discover traces of voice pathologies like dysph...
关键词：Dimensionality reduction dysphonia detection linear discriminant analysis logistic regression speech feature extraction support vector machine 
Highly Accurate Latouche-Ramaswami Logarithmic Reduction Algorithm for Quasi-Birth-and-Death Process
《Journal of Mathematical Study》2022年第2期180-194,共15页Guiding Gu Wang Li Ren-Cang Li 
National Natural Science Foundation of China(Grant Nos.11771100 and 12071332);NSF grant DMS-2009689;U-TA's Reserach Enhancement grant REP-270075;USDA grant 58-3070-0-006;NSF grants DMS-1719620 and DMS-2009689.
This paper is concerned with the quadratic matrix equation A_(0)+A_(1)X+A_(2)X^(2)=X where I-A_(0)-A_(1)-A_(2)is a regular M-matrix,i.e.,there exists an entrywise positive vector u such that(I-A_(0)-A_(1)-A_(2))u≥0 e...
关键词：Quadratic matrix equation M-MATRIX quasi-birth-and-death process minimal non-negative solution entrywise relative accuracy 
Highly Accurate Relations between the Fine Structure Constant and Particle Masses, with Application to Its Cosmological Measurement
《Journal of Modern Physics》2022年第5期682-699,共18页Frank R. Tangherlini 
Highly accurate algebraic relations between the fine structure constant a and a wide range of particle masses are given, ranging from Δa/a = (2.1 ±0.1)×10-7 to Δa/a = (-2.7 ±0.3 &...
关键词：Fine Structure Constant Particle Masses Proton-Electron Mass Ratio Cosmological Measurement 
Micellar sensitized catalytic kinetic spectrophotometry for highly accurate and reproducible determination of Ⅴ(Ⅳ) and Ⅴ(Ⅴ)被引量：2
《Rare Metals》2014年第4期466-478,共13页Ramazan Grkan Can Emektas 
financially supported by the Scientific Research Projects Council in Cumhuriyet University(No.294)
A highly accurate and reproducible micellar sensitized kinetic method was proposed for determination of V（VI）. The method is based on its catalytic effect on the oxidation of Coomassie brilliant blue R 250 （CBB＋）...
关键词：Vanadium speciation Kineticspectrophotometry BROMATE Coomassie brilliant blue R250 Micellar effect 
An accurate and highly-efficient performance evaluation approach based on queuing model for on-chip network被引量：1
《Science China(Information Sciences)》2013年第7期235-254,共20页LAI MingChe GAO Lei XIAO Nong WANG ZhiYing 
supported in part by National Basic Research Program (Grant No. 2007CB310901);National Science Foundation of China (Grant Nos. 60903039, 61103188, 61025009);Education Foundation of China(Grant No. 20094307120012)
An accurate and highly-efficient analysis approach is crucial for a designer to evaluate the perfor- mance of on-chip networks. To this end, the novel M/G/1/N queuing models that capture various blocking phenomenon of...
关键词：on-chip network model performance analysis 
Highly accurate SVM model with automatic feature selection for word sense disambiguation
《Journal of Systems Engineering and Electronics》2004年第4期723-727,共5页WangHao ChenGuilin XuLianxian 
A novel algorithm for word sense disambiguation(WSD) that is based on SVM model improved with automatic feature selection is introduced. This learning method employs rich contextual features to predict the proper sens...
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