Results 41 to 50 of about 2,465,255 (121)
Identification of a Zika NS2B epitope as a biomarker for severe clinical phenotypes. [PDF]
RSC Med Chem, 2021 Loeffler FF +14 more
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Embedding orthogonal partial Latin squares
, 1976 Two partial latin squares are orthogonal provided that when they are superimposed any ordered pairs obtained are distinct. The purpose of this paper is to show that any collection of pairwise orthogonal finite partial latin squares can be embedded into ...
Charles C. Lindner
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Mapping the dynamic transfer functions of eukaryotic gene regulation. [PDF]
Cell Syst, 2021 Lee JB +4 more
europepmc +1 more source
Rotaxane nanomachines in future molecular electronics. [PDF]
Nanoscale Adv, 2022 Wu P, Dharmadhikari B, Patra P, Xiong X.
europepmc +1 more source
Orthogonal-least-squares forward selection for parsimonious modelling from data
, 2009 The objective of modelling from data is not that the model simply fits the training data well. Rather, the goodness of a model is characterized by its generalization capability, interpretability and ease for knowledge extraction.
Sheng Chen, Chen, Sheng
core
ANALYTICAL FORLVIULAE Ai'll) ALGORITHMS FOR CONSTRUCTING MAGIC SQUARES FROM AN ARBITRARY SET OF 16 NUMBERS [PDF]
, 2005 In this paper we seek for an answer on Smarandache type question: may one create the theory of Magic squares 4x4 in size without using properties of some concrete numerical sequences?
CHEBRAKOV, Y.V.
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Orthogonal least squares methods and their application to non-linear system identification
, 1989 Identification algorithms based on the well-known linear least squares methods ofgaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modifiedGram-Schmidt, Householder transformation, Givens method, and singular valuedecomposition are ...
Luo, W., Chen, Sheng, Billings, S. A.
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, 2003 A new construction algorithm for multi-output radial basis function (RBF) network modelling is introduce by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design.
Hong, X., Harris, C.J., Chen, S.
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