RBF 神经网络自适应逼近源代码 RBF Adaptive Approximation

物元分析法及承载力指数验证法计算承载力源代码(Matter-element analysis and verification method to calculate the carrying capacity carrying capacity index source code)

对车辆图像进行一系列处理，有灰度变换，对比度增强，二值化，最后计算车辆实际高度(A series of image processing the vehicle, a gray-scale transformation, contrast enhancement, binarization, and finally calculate the actual height of the vehicle)

A digital modulation using simulink. very useful for beginer

程序中以一根接收天线为例，分别对一根发射天线、两根发射天线、三根发射天线和四根发射天线系统进行STBC仿真。比较误码率性能。(Program to a receiving antenna, for example, a transmitting antenna, respectively, the two transmit antennas, three transmit antennas and four transmit antenna system STBC simulation. Compare the bit error rate performance.)

主要内容：小波分析在语音信号处理、图象处理与编码、边缘提取与重建等(Main content: wavelet analysis in the speech signal processing, image processing and encoding, edge detection and reconstruction, etc.)

动画技术：电偶极子辐射的动态仿真,影片动画和实时动画。绘制各个时刻的电力线图，即使用contour函数在 t取不同值的情况下绘制电力线方程(Animation techniques: electric dipole radiation dynamic simulation, film animation and real-time animation. Rendering of each hour power line, which USES contour function in the wt take different values of electric draw equations )

matlab实验课件。详细介绍了matlab最基本的操作和功能，是两学期的内容。适合自学。(Matlab experiment courseware. Introduces in detail the matlab the basic operation and function, the contents of two semesters. Suitable for self-study.)

利用matlab编写，符合以下要求 1.鼠标点几点连成一个区域，填充颜色。 2.多次重叠交叉的区域填充(Use matlab write, meet the following requirements 1. Several mouse connected into an area filled with color. 2. Multiple overlapping cross the area fills)

说明：  仿真了4种常见多径衰落信道，包括无人机信道(The four common multipath fading channel, including the uav channel)

说明：  支持向量机最初用来解决模式识别问题，目的是发现泛化性能好的决策规则。然而，随着Vapnik的 不敏感损失函数的引入，支持向量机已经扩展为解决非线性回归估计问题，而且与神经网络方法相比，有着显著的优越性，被认为是人工神经网络方法的替代方法，已经成为目前机器学习领域的研究热点和焦点。(Support vector machine (SVM) was originally used to solve the problem of pattern recognition. However, with the introduction of Vapnik's insensitive loss function, support vector machine (SVM) has been extended to solve the problem of nonlinear regression estimation. Compared with neural network method, support vector machine (SVM) has obvious advantages. It is considered as an alternative method of artificial neural network method, and has become the research hotspot and focus in the field of machine learning.)