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[Algorithm] Meshless_SPH DL : 0: 使用fortran编写的无网格（光滑质点流体动力学）SPH算法-using FORTRAN prepared by the non-grid (smooth particle hydrodynamics) SPH algorithm
Date : 2025-12-24 Size : 114kb User : 殷水平
[Algorithm] nonliearequation DL : 1: 这是牛顿法求解非线性方程组哦那个，用matlab编写的3个m文件，F是方程组左端向量函数，JF是其Jacobian矩阵，最后调用newdim函数文件-This is the Newton method for solving nonlinear equations, oh, um, using Matlab prepared by the three m documents, F is equations extreme vector function, JF its Jacobian matrix, Call newdim function final document
Date : 2025-12-24 Size : 1kb User : 娄雯
[Algorithm] md DL : 0: The program md.f implements a simple molecular dynamics simulation in continuous real space. The velocity Verlet algorithm is used to implement the time stepping. The force and energy computations are performed in parallel, as is the time integration. (The program uses some Fortran90 features, so an F90 compiler may be needed.)
Date : 2025-12-24 Size : 2kb User : danielwood
[Algorithm] On-Line_MCMC_Bayesian_Model_Selection DL : 0: This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.-This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Date : 2025-12-24 Size : 215kb User : 晨间
[Algorithm] Reversible_Jump_MCMC_Bayesian_Model_Selection DL : 0: This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. -This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Date : 2025-12-24 Size : 340kb User : 晨间
[Algorithm] integrate(nu) DL : 0: This GUI can be used by entering nu at the MATLAB command prompt. The user can either select a function (f(x)) of their choice or a statistical distribution probability distribution function to plot over a user defined range. The function s integral can be evaluated over a user defined range by using: The composite trapezium, simpsons and gauss-legendre rules. This is useful for calculating accurate probabilities that one might see in statistical tables.
Date : 2025-12-24 Size : 12kb User : 徐亮
[Algorithm] waterfall_FFT DL : 0: 一个关于FFT应用的例子，This program calculates the Waterfall FFT of a time history，by Tom Irvine -With regard to the application of a FFT example, This program calculates the Waterfall FFT of a time history, by Tom Irvine
Date : 2025-12-24 Size : 2kb User : null
[Algorithm] DFP_algorithm DL : 0: DFP, 本程序适用于求解形如f(x)=1/2*x Ax+bx+c二次函数的稳定点 -DFP, this procedure applies to solution of the form f (x) = 1/2* x' Ax+ bx+ c quadratic function of the stable point
Date : 2025-12-24 Size : 1kb User : LiuMCH
[Algorithm] STRSCNE DL : 2: 给出变量的上下边界、初值和代价函数，能够搜索代价函数最小值时的变量取值。属于带约束的优化算法，可以用来求算非线性方程组。-STRSCNE is a Matlab code for constrained nonlinear systems of equations F(x)=0 l<=x<=u where F: R^n--> R^n, l and u are vectors of dimension n. Non-existent lower and upper bounds, i.e. entries of l and u equal to minus o plus infinity, are allowed. The algorithm is a globally convergent procedure that combines Newton method and an elliptical trust-region approach. The elliptical trust-region is defined employing a scaling diagonal matrix D and the trust-region subproblem is approximately solved by the dogleg method. Only strictly feasible iterates are generated. Various input/output options are provided, and we refer to the code itself for further documentation.
Date : 2025-12-24 Size : 5kb User : muxihan
[Algorithm] fdk-f DL : 1: 基于FDK的锥束CT全三维重建算法，Matlab语言版本。-FDK cone-beam CT based full three-dimensional reconstruction algorithm, Matlab language version.
Date : 2025-12-24 Size : 1kb User : 笑天
[Algorithm] RegressTest DL : 0: 回归显著性检验matlab程序。该函数可以求检验回归显著性的R值、F值。-Regression significance test matlab program. This function can seek significant resistance R value, F value of the regression.
Date : 2025-12-24 Size : 2kb User : lisa
[Algorithm] fft DL : 0: Matlab程序，GUI窗口用FFT程序计算有限长度正弦信号y=sin(2*pi*f*t) ,0<=t<=N*T-FFT program calculate the finite length of the sinusoidal signal y = sin (2* pi* f* t), 0 < = t < = N* T respectively the DFT results obtained and analyzed and discussed in the following cases: a) the signal frequency f = 50Hz, the sampling the credited with N = 32, the sampling interval T = 0.000625sb) signal frequency f = 50Hz, the sampling points of N = 32, the sampling interval T = 0.005sc), the signal frequency f = 50 Hz, the sampling points N = 32, the sampling interval T = 0.0046875sd) signal frequency f = 50Hz, the sampling points of N = 32, the sampled interval T = 0.004se) signal frequency f = 50Hz, the sampling points of N = 64, the sampling interval the T = 0.000625sf) signal frequency f = 250Hz, the sampling points N = 32, the sampling interval T = 0.005sg) c) a signal-post 32, to do a 64-point FFT
Date : 2025-12-24 Size : 12kb User : moumiao
[Algorithm] relirfF-code DL : 0: Code for Relief F algorithm, succesfully running on matlab 2010 b.
Date : 2025-12-24 Size : 1kb User : yelei
[Algorithm] GA1 DL : 0: 基于matlab的遗传多分搜索程序主程序为fmain 目标函数可以在f函数中修改-Matlab-based genetic multisection search program main program for fmain objective function can be modified in the function f
Date : 2025-12-24 Size : 3kb User : 邝晟
[Algorithm] adapt DL : 0: 通过matlab 实现{a，b}关于f（x）积分 -By matlab realize {a, b} on f (x) Credits
Date : 2025-12-24 Size : 3kb User : devon
[Algorithm] zhubuss DL : 0: MATLAB逐步搜索法计算方程的根. 逐步搜索法也称试算法.它是求方程f(x)=0的根的近似值位置的一种常用的方法. 逐步搜索法依赖于寻找连续函数)f(x)满足f(a)与f(b)异号的区间[a,b]一旦找到区间，无论区间多大，通过某种方法总会找到一个根。-MATLAB root search method gradually equation
Date : 2025-12-24 Size : 1kb User : matiejun
[Algorithm] bisect DL : 0: 二分法的Matlab程序实现。求解非线性方程f(x)=0的问题。而方程f(x)是多项式或超越函数又分为代数方程或超越方程。-Dichotomy Matlab program. Solving nonlinear equations f (x) = 0 problems. The equation f (x) is a polynomial or a transcendental function is divided into algebraic equations or transcendental equation.
Date : 2025-12-24 Size : 1kb User : 王军
[Algorithm] RelDielConst_SalineWater DL : 0: 用来计算海水相对介电常数的matlab程序，计算方法源自微波雷达遥感-computes the real and imaginary parts of the relative dielectric constant of water at any temperature 0<t<30, Salinity 0<S<40 0/00, and frequency 0<f<1000GHz
Date : 2025-12-24 Size : 1kb User : irene
[Algorithm] interpolation DL : 0: 定理1（介值定理）设函数f(x)在区间[a,b]连续，且f(a)f(b)<0，则方程f(x)=0在区间[a,b]内至少有一个根。(Theorem 1 (intermediate value theorem) set the function f (x) in the interval [a, b] continuous, and f (a) f (b) <0, then the equation f (x) =0 is at least one root in the interval [a and b].)
Date : 2025-12-24 Size : 1kb User : 粥多多
[Algorithm] f DL : 0: 雨流计数法读取txt文档中的2列数组，利用雨流计数法查找节点，输出原图像、极点图像、节点图像(Rain flow counting method Read out the 2 column array in the txt document, use the rain flow counting method to look up the node, output the original image, the pole image, the node image.)
Date : 2025-12-24 Size : 1kb User : malvina

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