Fuzzy-control-

This is a code for Noise level estimation in MATLAB

对初学者来说，泛函分析很难搞懂。这份资料就是关于泛函分析的，里面详细讲了泛函的来龙去脉。(For beginners, it is difficult to understand the functional analysis. This information is about the functional analysis, which details about the functional sequence of events.)

说明：  S-Function（系统函数）为扩展 Simulink?的性能提供了一个有力的工具。以下下节阐述了什么是S-Function，为什么可以使用 S-Function，以及怎样编写自己的 S-Function。(S-Function provides a powerful tool for extending the performance of Simulink. The following section explains what an S-Function is, why it can be used, and how to write your own S-Function.)

Optimum matlab implementation

Exponential distribution function by uniform distribution function

详细介绍了PID和模糊控制 专家控制 模糊自整定控制的原理和仿真(Details of the PID and fuzzy control fuzzy self-tuning expert control theory and simulation control)

基于能量检测的认知无线电感知频谱分析最优化设计(Based on energy detection sensing cognitive radio spectrum analysis to optimize the design)

Smooths a matrix (with/without NaN s) via recursive moving average method and eliminates data gaps. (MOVING_AVERAGE(X,F) smooths the vector data X with a boxcar window of size 2F+1, i.e., by means of averaging each element with the F elements at his right and the F elements at his left. The extreme elements are also averaged but with less data, obviously. Leaving the edges intact. The method is really fast. MOVING_AVERAGE2(X,M,N) smooths the matrix X with a boxcar window of size (2M+1)x(2N+1), i.e., by means of averaging each element with its surrounding elements that fits in the mentioned box centered on it. This one is also really fast. The elements at the edges are averaged too, but the corners are left intact. NANMOVING_AVERAGE(X,F) or NANMOVING_AVERAGE(X,F,1) accept NaN s elements in the vector X the latter interpolates also those NaN s elements surrounded by numeric elements. NANMOVING_AVERAGE2(X,M,N) or NANMOVING_AVERAGE2(X,M,N,1) accept elements NaN s in the matrix X the latter interpolates also those NaN elements surrounded by numeric elements.)

MATLAB在LabVIEW开发虚拟仪器中的应用研究(MATLAB LabVIEW )

31个城市的VRP进行蚁群算法求解的matlab源码(31 cities, ant colony algorithm for VRP to the matlab source code)