ordinary differential equationS
標(biāo)簽： differential equationS ordinary
上傳時(shí)間： 2013-12-23
上傳用戶：Ants
Partial differential equationS
標(biāo)簽： differential equationS Partial
上傳時(shí)間： 2014-11-22
上傳用戶：hfmm633
forward euler solving differential equationS
標(biāo)簽： differential equationS forward solving
上傳時(shí)間： 2013-12-24
上傳用戶：h886166
Solving nonlinear equationS using Newton s and Transversal methods for function x=exp(-x^2)
標(biāo)簽： Transversal nonlinear equationS function
上傳時(shí)間： 2017-09-28
上傳用戶：aix008
Solving linear equationS using iteration. Seidels and Biggest incline methods
標(biāo)簽： equationS iteration Solving Seidels
上傳時(shí)間： 2013-12-25
上傳用戶：playboys0
Solving integration and differential equationS
標(biāo)簽： differential integration equationS Solving
上傳時(shí)間： 2013-12-28
上傳用戶：zhuimenghuadie
Simultaneous Displacement Method for a linear equationS system
標(biāo)簽： Simultaneous Displacement equationS Method
上傳時(shí)間： 2013-12-19
上傳用戶：caiiicc
Abstract: A resistive feedback network is often used to set the output voltage of a power supply. A mechanical potentiometer (pot)conveniently solves the problem of adjusting a power supply. For easier automatic calibration, a mechanical pot can be replaced witha digital pot. This application note presents a calibration solution that uses a digital pot, because digipots are smaller, do not movewith age or vibration, and can be recalibrated remotely. This proposed solution reduces the susceptibility of the system to thetolerance of the digital pot's end-to-end resistance, making the solution optimal fordesigners. This application note also explainssome of the equationS required to calculate the resistor chain values and to use a digital pot in this way. A spreadsheet withstandard reisistor values is available for easy calculations.
標(biāo)簽： 電源供應(yīng)器 數(shù)字電位器 應(yīng)用筆記 校準(zhǔn)
上傳時(shí)間： 2013-10-31
上傳用戶：caiguoqing
OFELI is an object oriented library of C++ classes for development of finite element codes. Its main features are : * Various storage schemes of matrices (dense, sparse, skyline). * Direct methods of solution of linear systems of equationS as well as various combinations of iterative solvers and preconditioners. * Shape functions of most "popular" finite elements * Element arrays of most popular problems (Heat Transfer, Fluid Flow, Solid Mechanics, Electromagnetics, ...).
標(biāo)簽： development oriented classes element
上傳時(shí)間： 2015-03-03
上傳用戶：kbnswdifs
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equationS are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
標(biāo)簽： instantaneous algorithm Bayesian Gaussian
上傳時(shí)間： 2013-12-19
上傳用戶：jjj0202
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