Dijkstraandprocedures

一种遗传优化神经网络的算法，里面包含有初始化函数,在运行程序前先将实验数据load进去。输入A =load( D:数据.txt ) 这里的D是你存储数据的位置(A genetic optimization of neural network algorithm, which contains the initialization function, before running the program to the experimental data in load. Enter the A =load (D: data.Txt) where D is your data storage location)

matlab实现二维数组的fft变化，得到时域图、幅频域图。(fft change implementation, time domain, frequency domain amplitude, is a two-dimensional array of the FFT changes)

The following Matlab project contains the source code and Matlab examples used for detect rfid random . detect rfid random by id

HMM and Gaussian functions and speech recognition..

这个matlab源程序 系统详细的描述了 滤波器模型的计算方法(The matlab source system, a detailed description of the calculation method filter model)

this ismatlab code for mpc example..

：介绍了扩展卡尔曼滤波算法和无迹变换(unscented transformation，UT)算法，并对扩展卡尔曼滤波算法(EKF)和无 迹卡尔曼滤波算法(UKF)进行比较，阐明了UKF优于EKF。在此基础上，提出了一种基于Unscented变换(uT)的高斯和滤 波算法，该算法首先通过合并准则得到适当个数的混合高斯模型，逼近系统中非高斯噪声的概率密度(: Introduction of the extended Kalman filter algorithm and unscented transform (unscented transformation, UT) algorithm, the extended Kalman filter algorithm (EKF) and unscented Kalman filter (UKF) for comparison to clarify the UKF is superior to EKF. On this basis, we propose an approach based on Unscented Transform (uT) and the Gaussian filtering algorithm, which first of all, by merging the appropriate number of criteria to be a mixture of Gaussian model, which was close to the system of the Central African Gaussian noise probability density)

Digital communication labs,

一些高等数学应用方面的小实验，都运行过的，包括积分变换，解微分方程，差值等，适合matlab初学者。(Some applications of higher mathematics a small experiment, run-off, including the integral transform, solution of differential equations, difference, etc., suitable for matlab beginners.)

在MATLAB实现的用C实现的KNN算法，输入训练数据文件，和test文件，进行预测分类，并且可以与真实情况比较测试预测正确百分比(Implemented in MATLAB KNN algorithm implemented in C, the input training data file, and test files, to predict the classification and testing with the real situation is more correct percentage of predicted)