Iteration
共 21 篇文章
Iteration 相关的电子技术资料，包括技术文档、应用笔记、电路设计、代码示例等，共 21 篇文章，持续更新中。
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
MATLAB之父《编程实践 》中译本 带书签目录
<p>MATLAB之父 编程实践 中译本__PDF电子书下载 带书签目录 完整版</p><p>目 录</p><p>第1 章迭代（Iteration） 1<br/></p><p>第2 章斐波那契数（Fibonacci Numbers） 15<br/></p><p>第3 章日历与时钟（Calendars and Clocks） 29<br/></p><p>第4 章矩阵（Matr
Fixed-Point iteration
Fixed-Point iteration
％ 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
matlab function ---> find roots using fixed-point iteration
matlab function ---> find roots using fixed-point iteration
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－Schmid
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 o
Based on Matlab,Gauss Iteration Method
Based on Matlab,Gauss Iteration Method
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 est
这个代码是policy iteration算法关于强化学习的. 请您用winzip 解压缩
这个代码是policy iteration算法关于强化学习的. 请您用winzip 解压缩
The False-Position method to solve a linear equation The Bisection method to solve linear equation
The False-Position method to solve a linear equation The Bisection method to solve linear equation Jacobi Iteration on a 3D plane
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-simil
computing singular value of matrix by iteration
computing singular value of matrix by iteration
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 versi
The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Proces
The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some varia
Solving linear equations using iteration. Seidels and Biggest incline methods
Solving linear equations using iteration. Seidels and Biggest incline methods
calculatePXTheta---Calculate the probability of each pixel being its color conditioned on all of the
calculatePXTheta---Calculate the probability of each pixel being its color conditioned on all of the clusters that were found at the previous (coarser) iteration.
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 s
Matrix Iteration Methods. Matlab Implementation.
Matrix Iteration Methods. Matlab Implementation.
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_f