Methods: numerical: data analysis
Data Smoothing Numerical Methods and Their Applications in Unsupervised Learning for Prediction of Diabetes in Patients
... functional data analysis using curves and error estimation was first introduced by Ramsay (1982) in his paper “When the Data are Functions” [4], prior to that in recent decades, many researchers have ...
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Statistical Methods of Neuroimaging Data Analysis.
... We make a few remarks about the above optimization procedure. First, although the objective value decreases monotonically through iterations, the convergence to a global optimum is not guaranteed, since Eq. 2.5 involves ...
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Graphical methods for the analysis of data
... where the ct^) are unknown parameters and gr (x) is a known polynomial of degree r in x which is fixed for the particular data under consideration. In deciding the value of h, the order of the polynomial fit, it ...
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Tensor numerical methods for multidimensional PDES: theoretical analysis and initial applications
... essential data compression using representations in low-rank tensor formats and, hence, to the efficient O(log N)-approximation method? The constructive answer is formulated by the QTT approximation theory proven ...
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Numerical methods for the interpolation and approximation of data by spline functions
... error analysis Bjftrck ( 1967 ) concluded th a t, regardless o f whether or not interchanges are made, the errors in the computed solution are less than the errors re s u ltin g from r e la t iv e perturbations in ...
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Adopting the Multiresolution Wavelet Analysis in Radial Basis Functions to Solve the Perona-Malik Equation
... sampled data and image restoration [3,4]. As with other meshless methods, RBF have been frequently used for the numerical solution of PDEs and their extensive use in numerical analysis ...
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Clusterers: a comparison of partitioning and density-based algorithms and a discussion of optimisations
... clustering methods within the partitioning family; K-means converts data to nu- merical points on a set of axes and calculates the numerical mean of these points to dictate cluster centroids [10], K- ...
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Numerical methods for stress analysis using known elasticity solutions
... Data input Areas of elements Stiffness matrix Trial and loading functions Stress fields of Boundary conditions Strain energy term Correction to matrix D Solution of the equations Trial f[r] ...
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Fracture Analysis of Delaminated Composite Beams Using Analytical and Numerical Methods
... Vibration Analysis of Delaminated Composite Laminates in Prebuckled States Based on a New Constrained Model by Hsin- Piao Chen, John ...test data have been ...
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Numerical Methods in Site Response Analysis for Nuclear Applications
... response analysis programs are typically validated by comparing the numerical response of a real soil profile to recorded field ...field data (Chang, 1996; Idriss, 1990) but these data either ...
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Shape Function for Mesh Free Methods Using Moving Least- Squares Approximation Prof. Sanjaykumar D. Ambaliya , Prof. Pradip V. Savaliya
... The selection of the weighting function plays a very vital role in the formulation and solution of meshfree methods. It is concluded that the cubic spline weighting function gives the shape function which possess ...
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Adaptive grid methods for Q-tensor theory of liquid crystals : a one-dimensional feasibility study
... important numerical analysis issues which the study of such materials ...difficult numerical challenges to those trying to simulate the real-life dynamic situations which are of interest in an ...
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Network based Reconfigurable CNC System Technology with On machine Monitoring and Intelligent Maintenance
... The data acquisition, its preliminary analysis and storage are all completed on the numerical control system, and the numerical control system realizes the corresponding machine running status ...
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Quadratic spline solution of Calculus of Variation Problems
... Razzaghi and Marzban [8] introduced a new direct computational method via hybrid of Block-Pulse and Chebyshev functions to solve variational problems. Then, Razzaghi et al. [9, 10] presented direct methods for ...
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Statistical Analysis Methods for the fMRI Data
... the analysis of neuroimag- ing data was first proposed by Friston et ...fMRI data analysis techniques employed by neuroscientists use a GLM of one form or ...statistical analysis which ...
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Methods for The Metagenomic Data Visualization and Analysis
... of data with drawing every group as a circle and marking special taxa of interest with dedicated ...for analysis of metagenomic data, MEGAN (Huson, 2016) can visually represent taxonomic abundance of ...
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Statistical methods for analysis of genetic data
... NGS holds enormous promise for the study of mutations, copy number alterations and structural variants, including fusion genes (Ding et al., 2010). The discovery of mutations that determine phe- notypes is a fundamental ...
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Comparison of numerical techniques in solving transient analysis of electrical circuits
... transient analysis of electrical circuit is analysed using analytical method and RK-4 ...transient analysis can be done systematically and ...transient analysis is only done for series RLC circuit in ...
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... Hence, numerical procedures like the finite difference method and the finite element techniques have been developed to yield approximate solutions to boundary value problems of engineering and mathematical physics ...
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A Survey of Regularization Methods of Solution of Volterra Integral Equations of the First Kind
... the methods for Volterra equations of the first kind are not nearly as ill-posed as methods for Fredholm integral equations of the first ...regularization methods with a view to identifying the ...
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