Latest Research News on Vector Space : April 21

Posted on April 24, 2021Categories Mathematics and Computer ScienceTags   Leave a comment on Latest Research News on Vector Space : April 21

[1] Space vector PWM control of dual three-phase induction machine using vector space decomposition The technique of vector space decomposition control of voltage source inverter fed dual three-phase induction machines is presented in this paper. By vector space decomposition, the analytical modeling and control of the machine are accomplished in three two-dimensional orthogonal subspaces and the dynamics of the electromechanical energy conversion related and the nonelectromechanical energy conversion related machine variables are thereby totally decoupled. A space vector PWM technique … Continue reading “Latest Research News on Vector Space : April 21”

Latest Research on Artificial Neural Network: March – 2020

Posted on March 7, 2020Categories Mathematics and Computer ScienceTags   Leave a comment on Latest Research on Artificial Neural Network: March – 2020

Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences Artificial neural networks are appearing as useful alternatives to traditional statistical modelling techniques in many scientific disciplines. This paper presents a general introduction and discussion of recent applications of the multilayer perceptron, one type of artificial neural network, in the atmospheric sciences. [1] Logistic regression and artificial neural network classification models: a methodology review Logistic regression and artificial neural networks are the models of choice in many medical data classification tasks. In … Continue reading “Latest Research on Artificial Neural Network: March – 2020”

Latest News on Fourier Coefficients Research: Dec – 2019

Posted on December 3, 2019Categories Mathematics and Computer ScienceTags ,   Leave a comment on Latest News on Fourier Coefficients Research: Dec – 2019

Improved Fourier coefficients for maps using phases from partial structures with errors Unrefined or partly refined models of macromolecules square measure usually incomplete and usually have giant coordinate errors. it’s shown that section likelihood equations applicable for an ideal partial structure cause inaccurate estimates of section possibilities in such cases. Therefore, it’s necessary to use equations that are derived granting errors within the partial structure. a technique is given to estimate the parameter [sigma]A in these section likelihood expressions from … Continue reading “Latest News on Fourier Coefficients Research: Dec – 2019”

Latest Research on Optimal Control Approach: Nov – 2019

Posted on November 28, 2019Categories Mathematics and Computer ScienceTags ,   Leave a comment on Latest Research on Optimal Control Approach: Nov – 2019

An optimal control approach to a posteriori error estimation in finite element methods This article surveys a general approach to error management and reconciling mesh style in Galerkin finite component strategies that’s supported duality principles as utilized in best management. Most of the prevailing work on a posteriori error analysis deals with error estimation in world norms just like the ‘energy norm’ or the L2 norm, involving sometimes unknown ‘stability constants’. However, in most applications, the error in a very … Continue reading “Latest Research on Optimal Control Approach: Nov – 2019”

Latest Research News on Linear Equation: Nov – 2019

Posted on November 19, 2019November 19, 2019Categories Mathematics and Computer ScienceTags ,   Leave a comment on Latest Research News on Linear Equation: Nov – 2019

The reduced linear equation method in coupled cluster theory. A numerical procedure for expeditiously determination giant systems of linear equations is given. The approach, termed the reduced equation (RLE) methodology, is illustrated by determination the systems of linear equations that arise in linearized versions of coupled‐cluster theory. The nonlinear coupled‐cluster equations are treated with the RLE by presumptuous Associate in Nursing approximate linearization of the nonlinear terms. terribly economical convergence for linear systems and sensible convergence for nonlinear equations area … Continue reading “Latest Research News on Linear Equation: Nov – 2019”

Latest Research News on Convergence Analysis: Oct – 2019

Posted on October 28, 2019Categories Mathematics and Computer ScienceTags ,   Leave a comment on Latest Research News on Convergence Analysis: Oct – 2019

Convergence analysis of canonical genetic algorithms This paper analyzes the convergence properties of the canonical genetic algorithmic rule (CGA) with mutation, crossover and proportional copy applied to static optimisation issues. it’s verified by suggests that of homogenized finite Markov chain analysis that a CGA can ne’er converge to the world optimum notwithstanding the data format, crossover, operator and objective operate. however variants of CGA’s that continually maintain the simplest answer within the population, either before or when choice, ar shown … Continue reading “Latest Research News on Convergence Analysis: Oct – 2019”

Latest Research News on Epidemic Model Research: Sep – 2019

Posted on September 24, 2019Categories Mathematics and Computer ScienceTags ,   Leave a comment on Latest Research News on Epidemic Model Research: Sep – 2019

A generalization of the Kermack-McKendrick deterministic epidemic model In this paper the Kermack-McKendrick settled model is generalized, introducing associate degree interaction term during which the dependence upon the quantity of infectives happens via a nonlinear delimited operate which can take into consideration saturation phenomena for giant numbers of infectives. associate degree extension of the well-known threshold theorem is obtained, once a stability analysis of the equilibrium points of the system. A numerical example is dispensed well. [1] Pulse vaccination strategy … Continue reading “Latest Research News on Epidemic Model Research: Sep – 2019”