original-code-of-Matlab-Neural-Network

遗传融合的自适应蚁群算法最优PID控制研究(Genetic fusion of adaptive ant colony algorithm optimal PID control)

基于MATLAB的 Floyd最短路算法(MATLAB-based shortest path algorithm of Floyd)

支持向量机导论 matlab中支持向量机算法的入门级经典教材(Introduction to matlab support vector machine support vector machine algorithm is the classic entry-level teaching materials)

与MIe散射理论配套使用的用于测定mie散射光强，采用matlab编程实现(Mie intensity)

这个Matlab图形用户界面允许用户计算圆形，椭圆形和任意形状的广义极化张量。此计算的近似算法，该算法是基于Capdeboscq等人开发出一种方法。 (This Matlab GUI allows the user to compute the GPT of disks, ellipses, and arbitrary imported shapes. The approximating algorithm that does this computation is based off a method developed by Capdeboscq et al. )

在MATLAB环境下用程序实现IIR,FIR滤波器的设计，无需使用系统自带设计工具，具备选窗，阶数选择，频带选择等功能。(Program in the MATLAB environment to achieve IIR and FIR filter design, without the use of the system comes with a design tool with the selected window, order selection, band selection and other functions.)

Cumulant-Based Inverse Filter Criteria

Using high-order cumulants of MPSK signal modulation recognition, Calculated transmission characteristics and reflection characteristics of the one-dimensional photonic crystals, Principal component analysis of multivariate data analysis projection.

为了提高使用精度，研究了某型号MEMS陀螺仪的随机漂移模型。采用游程检验法分析了 该陀螺仪随机漂移数据的平稳性，并根据该漂移为均值非平稳、方差平稳的随机过程的结论， 采用梯度径向基（RBF）神经网络对漂移数据进行了建模。实验结果表明：相比经典RBF网络模 型而言，这种方法建立的模型能更好地描述MEMS陀螺仪的漂移特；相对于季节时间序列模型而 言，其补偿效果提高了大约15％。(In order to improve accuracy, to study a particular model of the MEMS gyroscope random drift model. Using run-length analysis of the test gyro random drift data stationarity, and in accordance with the drift for the average non-stationary, the variance of the random process a smooth conclusion, the use of gradient radial basis (RBF) neural network drift data to build mode. The experimental results show that: compared to the classical RBF network model, this method of establishing a model to better describe the MEMS gyroscope drift special compared with the seasonal time series model, the effect of their compensation increased by approximately 15.)

for solving TSP in matlab using hopfield neural network