FEM-Matlab

paper on Volterra Filtering Techniques for Removal of Gaussian and Mixed Gaussian-Impulse Noise

音乐合成 内容：1) 自己朗诵一段文字，并录制成.wav 文件； 2) 利用 matlab，给这段录音添加背景音乐； 代码都嫁了注释(use matlab, add background music to the recording which you read a text )

基于煤耗特性曲线的遗传算法1、运行主程序main，可根据需求修改相关参数，进行迭代； 2、每次修改数据或参数可修改储存的文件名称，以保存迭代数据； 3、运行Result输入要导出的储存文件的名称可得到相应的适应度函数曲线，适应度函数最小值和三个变量取值； 4、将上述三个变量值输入到huatu.m中，即可得到拟合的曲线图。(Genetic Algorithms Based on Coal Consumption Characteristic Curve)

model of type 1 subcat. sensor

matlab滑动滤波程序，读入text直接实现滤波(failed to translate)

这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of pseudo-inputs or basis vectors for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the pseudo-inputs , with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. spgp_lik is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using spgp_pred . I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing the hyperparameters sensibly. Its current limitations are that 1) it is slow and memory intensive for high dimensional data sets 2) it is heavi)

QaM在加性高斯白噪声下的系统仿真模型，使用的是simulink(QAM in additive white Gaussian noise of system simulation models, using simulink)

用matlab 实现求二维泊松方程解的过程(Seeking to achieve with two-dimensional Poisson equation matlab solution process)

计算梁的固有振型额的有限元方法a FEM program to solve the models of a beam(a FEM program to solve the models of a beam)

Genetic algorithm developed with PSO