carrier-MQW

内燃机转子仿真，转子裂纹等对转子性能影响做了详细分析(Simulation of the internal combustion engine rotor, rotor cracks on the rotor performance to do a detailed analysis of)

RLS算法去除加噪声音乐程序，效果比较好，有图为证。(RLS algorithm to remove noise adding music program, the effect is better, has a license to the graph. )

里面有MATLAB的SVM工具箱和基于wine的数据分类程序源代码，可实现数据的分类(SVM Toolbox of MATLAB)

自己写的，模式识别最近邻算法实现，配有IRIS数据集，非常实用(Their own writing, pattern recognition, nearest neighbor algorithm, with IRIS data set, very useful)

a gain calculator about semiconductor optical amplifier gain and ode method

C_C方法，本函数用于求延迟时间tau和时间窗口tw(C_C method, this function is used to find the delay time tau and the time window tw)

无速度传感器matlab仿真模型，带测试模型(No speed sensor matlab simulation model with test model)

说明：  用matlab编写的几个小程序，有关于矩阵的计算，神经网络的训练。数据的输入输出等。(Matlab prepared with a few small procedures have on the calculation of the matrix, neural network training. Such as data input and output.)

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete introductory discussion can be found in [Sorenson70], which also contains some interesting historical narrative.(In 1960, R. E. Kalman published his famous paper describ ing a recursive solution to the discretedata li near filtering problem [Kalman60]. Since that time, due in large part to advances in digital computi Vi, the Kalman filter has been the subject of extens ive research and application. particularly in the area of autonomous or assis ted navigation. A very "friendly" introductio n to the general idea of the Kalman filter can be f ound in Chapter 1 of [Maybeck79] while a more complete introductory discussion can be found in [Sorenson70] which also contains some interesting historic al narrative.)

使用网格离散化的方法对带有障碍物的环境建模，使用邻接矩阵存储该环境，使得问题转化为蚁群算法寻找最短路径。(Using a grid discretization method modeling environment with obstacles, the environment, the adjacency matrix storage problem into the ant colony algorithm to find the shortest path.)