Matlab_Manual

智能控制算法，小脑模型，神经网络，函数逼近(Intelligent control algorithm, cerebellar models, neural networks, function approximation)

多项式和非多项式曲线拟合，MATLAB的经典案例 (Polynomial and non polynomial curve fitting)

此程序用于计算高光谱数据中Linear extrapolation法计算植被红边位置(This program used to calculate the spectral data Linear extrapolation method of vegetation red edge position)

数值分析程序中的一个例子，matlab gui编程(Numerical analysis of an example program, matlab gui programming)

matlab与VC混合编程，输入方程，与自变量范围，就可以计算方程的值，与倒竖值。(mixed programming with VC matlab input equation, and the scope of the independent variables, we can calculate the value equation, and the inverted vertical value.)

基于MUSIC的空间谱估计算法。使用均匀线阵。提供了解相干信号的前向平滑，双向平滑算法。(MUSIC spatial spectrum estimation algorithm. Using uniform linear array. Understand the coherent signal smoothing, double smoothing algorithm.)

一段可以借鉴的增强图像效果的matlab代码，能达到很好的效果，可以参考。(Some can learn from the matlab code, can achieve good results, you can reference.)

基于matlab的BOC信号的自相关函数，阶数n可以自定义，正余弦相位也可以自定义；CBOC的自相关函数程序-MATLAB based on, BOC_ACF, n_order,CBOC_ACF,亲测有效(Autocorrelation function of BOC signal based on matlab, order number n can customize, cosine phase can also custom CBOC autocorrelation function of the program- MATLAB-based on, BOC_ACF, n_order, CBOC_ACF, effective measurement)

说明：  Hu不变矩基础实现，七个不变矩，仅计算不变矩，未计算相似度(Hu imdidndaidndansjncisancicn)

基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。(Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55 , which reduces also the delay and increases the throughput.)