OOK_NonCoherent_ThresholdChoice

偏微分方程组的求解，使用偏微分代码直接求解。(Solving partial differential equations, using partial differential code directly solved.)

MATLAB7.1的关于遗传算法的所有源程序详解及其变异算法(MATLAB7.1 all about the source of genetic algorithms and its variation Detailed Algorithm )

加入重复控制，是机器学习的例程，用于信号特征提取、信号消噪。( Join repetitive control, Machine learning routines, For feature extraction, signal de-noising.)

人工产生scurve数据集，方便一些降维方法的效果验证(Scurve generate artificial data sets to facilitate some of the effects of dimensionality reduction methods to verify)

深度搜索，可将边缘断点连接起来，多用于图像分割中和边缘检测结合使用(Depth of search, could be the edge connecting the breakpoints are used for image segmentation and edge detection used in conjunction)

高斯白噪声信道下原信号的误码率特性，仅供参考(Gaussian white noise channel bit error rate characteristics of the original signal)

this is about matlab code for modeling solid

matlab神经网络工具箱中的函数用法的介绍(the introduction of the Matlab neural network toolbox function usage)

This AttributeVisitor marks all methods that catch exceptions.

功率谱估计的应用范围很广，在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法；经典谱估计是基于傅立叶变换的，虽然具有运算效率高的优点，但是频谱分辨率低同时旁瓣泄漏严重，对长序列有着良好的估计。为了克服经典谱估计的缺点，人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的，有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高，同经典谱估计互为补充。在认真学习了现 代谱估计方法后，我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。(Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe)