design

Extended Kalman Filter MATLAB code

matlab各种插值算法应用实例,包括：拉格朗日插值、艾特肯插值法、牛顿插值法、 高斯插值法、 埃尔米特插值法、 分段埃尔米特插值法、样条插值、有理分式插值法、分片双线性插值、二元三点拉格朗日插值及分片双三次埃尔米特插值等等(a variety of interpolation algorithm matlab application examples include: Lagrange interpolation, Aitken interpolation, Newton interpolation, Gauss interpolation, Hermite interpolation, sub-Hermite interpolation, spline interpolation, rational fraction interpolation piecewise bilinear interpolation, dual three-point Lagrange interpolation and piecewise bi-cubic Hermite interpolation, etc.)

matlab实现的深度学习代码，autocode(a code for deeplearing,autocode)

说明：  电力系统负荷预测研究综述与发展方向的探讨(Review of Power System Load Forecasting and the development of)

利用MATLAB软件，通过编程来计算计算卫星坐标，通过输入相关参数之后就可以给出卫星的坐标(Using MATLAB software, programmed to calculate the coordinates of the satellite is calculated by the following input parameters can be given the coordinates of the satellite)

用于阵列信号处理的常用代码 包括经典处理和自适应处理 代码准确无误都能运行 可读性强(matlab code for array processing)

功率谱密度相关方法的MATLAB实现代码，包含基础讲解和算例代码(Power spectral density related methods of MATLAB code, including basic explanation and example code)

This example application shows you how to use Real-Time Workshop Embedded Coder to target a dual core Blackfin microprocessor. The complete build is managed by a template makefile and control over the memory regions is provided by custom storage classes. The example imposes a top level architecture on the model to define the split of model code between the two cores. This document describes a complete run-through of the model from Simulink simulation to code simulation using VisualDSP. I think it will take about 1 hour to go through the example once you have VisualDSP installed.

说明：  珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。 三、判断聚类是否合理 采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps: A, initialize clustering center 1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center. 2, with former C a sample as the initial clustering center. 3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center. Second, initial clustering 1, according to the sample into the nearest principle clustering center represents the class. 2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class. Three, judge clustering is reasonable Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)

this code is matlab code that generate fractal shapes.