xiaobo

相关噪声模型和相关函数计算 相关函数是平稳随机过程的重要数字特征，根据观测记录的信号波形或者一串数据序列，来估计该信号的自相关函数是信号处理的重要方法之一。(correlation noise model and correlation function)

采用Matlab工具箱函数建立神经网络，对一些基本的神经网络参数进行了说明，深入了解参考Matlab帮助文档。 (Using Matlab toolbox functions to establish neural networks, some of the basic neural network parameters are described to understand the reference to Matlab help documentation.)

Alamouti space time coding simulation Maximal Ratio Combining BER simulation

matlab源程序 比较直传，AF，DF的误码率仿真 比较理论误码率和直传误码率仿真曲线图 适合初学者阅读(matlab source code comparison forward pass, AF, DF bit error rate BER simulation and comparison theory forward pass BER curves for beginners to read)

使用svm进行数据的预测，首先进行pca对数据进行主元分析，提取有用信息，结果显示数据拟合效果非常好(SVM is used to predict data. first, PCA is used to analyze the data and extract useful information. the results show that the data fitting effect is very good.)

粒子滤波技术在非线性、非高斯系统表现出来的优越性，决定了它的应用范围非常广泛。另外，粒子滤波器的多模态处理能力，也是它应用广泛有原因之一。国际上，粒子滤波已被应用于各个领域。在经济学领域，它被应用在经济数据预测；在军事领域已经被应用于雷达跟踪空中飞行物，空对空、空对地的被动式跟踪；在交通管制领域它被应用在对车或人视频监控；它还用于机器人的全局定位。 (Particle filter technology in the non-linear, non-Gaussian system demonstrated the superiority of the decision of its wide range of applications. In addition, the particle filter for multimodal capabilities, also has one of the reasons it is widely used. Internationally, the particle filter has been applied to various fields. In economics, it is applied to forecast economic data in the military field have been applied to radar tracking aerial flying objects, air to air, air-passive tracking in the field of traffic control it was used in the car or the person video monitoring also used the global positioning robot.)

本代码主要用了多标签K近邻方法（MLKNN）实现对多标签数据进行分类(This code mainly spent more than a label K-nearest neighbor method (MLKNN) to achieve the multi-label data classification)

最近邻聚类算法，是经典的聚类算法，能够很好的实现，相信对大家有帮助(Nearest neighbor clustering algorithm)

关于 MATLAB 图像加密的讲解 和 图像处理 的内容 很详细(On the MATLAB image encryption and image processing to explain in great detail the contents of the)

This is a our final year project that we did for for the partial fulfillment of BSc degree in Electrical Engineering.