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数学计算 Using Jacobi method and Gauss-Seidel iterative methods to solve the following system The require
Using Jacobi method and Gauss-Seidel iterative methods to solve the following system
The required precision is   =0.00001, and the maximum iteration number N=25. Compare the number of iterations and the convergence of these two methods
技术资料 LuaXML 源码
LuaXML provides a minimal set of functions for the processing of XML data in Lua. It offers a
very simple and natural mapping between the XML data format and Lua tables, which
allows one to parse XML data just using Lua's normal table access and iteration
methods.
数学计算 数值线性代数的Matlab应用程序包 共13个程序函数
数值线性代数的Matlab应用程序包
共13个程序函数，每个程序函数有相应的例子函数一一对应，以*Example.m命名
程序名称 用途 Method 方法
GrmSch.m QR因子分解 classical Gram－Schmidt orthogonalization 格拉母－斯密特
MGrmSch.m QR因子分解 modified Gram－Schmidt iteration 修正格拉母－斯密特
househol ...
文章/文档 A fractal is generally "a rough or fragmented geometric shape that can be split into parts, each of
A fractal is generally "a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole,"[1] a property called self-similarity. The term was coined by Beno&#238 t Mandelbrot in 1975 and was derived from the Latin fractus ...
数值算法/人工智能 program to solve a finite difference discretization of Helmholtz equation : (
program to solve a finite difference discretization of Helmholtz equation :
(d2/dx2)u + (d2/dy2)u - alpha u = f using Jacobi iterative method.
COMMENTS: OpenMP version 3: 1 PR outside the iteration loop, 4 Barriers
Directives are used in this c ...
生物技术 This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise
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 ...
文件格式 Rao-Blackwellised Particle Filters (RBPFs) are a class of Particle Filters (PFs) that exploit condi
Rao-Blackwellised Particle Filters (RBPFs) are a class of Particle
Filters (PFs) that exploit conditional dependencies between
parts of the state to estimate. By doing so, RBPFs can
improve the estimation quality while also reducing the overall
computational load in comparison to original PFs. Howev ...
人工智能/神经网络 ％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is p
％ Train a two layer neural network with the Levenberg-Marquardt
％ method.
％
％ If desired, it is possible to use regularization by
％ weight decay. Also pruned (ie. not fully connected) networks can
％ be trained.
％
％ Given a set of corresponding input-output pairs and an initial
％ network,
％ ...
matlab例程 ％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input da
％ EM algorithm for k multidimensional Gaussian mixture estimation
％
％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ ...
人工智能/神经网络 function [U,center,result,w,obj_fcn]= fenlei(data) [data_n,in_n] = size(data) m= 2 ％ Exponent fo
function [U,center,result,w,obj_fcn]= fenlei(data)
[data_n,in_n] = size(data)
m= 2 ％ Exponent for U
max_iter = 100 ％ Max. iteration
min_impro =1e-5 ％ Min. improvement
c=3
[center, U, obj_fcn] = fcm(data, c)
for i=1:max_iter
if F(U)>0.98
break
else
w_new=eye(in_n,in_n)
center1=sum(cent ...