生成shepp-logan 三维头模型

gold序列用于跳频通信，给出了gold序列生成跳频序列的生成函数，并给出高斯白噪声和多用户干扰下的误码率曲线。(gold sequence for frequency hopping communications, give the gold sequence generated hopping sequence generation function, and to give white Gaussian noise and multi-user interference of the bit error rate curve.)

热处理融合，崭新的融合处理方法，仿真显示性能得到有效提升(Heat treatment, a new fusion processing method, the performance of the simulation show that ascension)

通过学习CRC编码原理，本部分建立了SIMULINk模型，实现了CRC编译码。(in this part we build the simulink modol of the encoded and decoded of CRC.we can more understand the code)

学习别人做的 很简请前辈看看，指教，谢谢大家！(学习被人做的 很简请前辈看看，指教，谢谢大家！)

基于matlab程序对医疗保险费用进行测算，对于医疗保险费用的测算很有帮助(Based on the matlab program to calculate the cost of medical insurance, medical insurance costs for the estimated useful)

svpwm model of 3-level npc invertersvpwm model of 3-level npc invertersvpwm model of 3-level npc invertersvpwm model of 3-level npc invertersvpwm model of 3-level npc inverter

利用yuler-walker方法预测AR参数，其中第二部用到了一维线性扫描确定参数。(The yuler-walker method to predict the AR parameters, the second part of which used a one-dimensional linear scan to determine the parameters.)

matlab神经网络手册，想打印出来看的可以下载哦(matlab neural network handbook, would like to print out looking at can download Oh)

30个MATLAB学习的案例，神经网络的实用例子(30 MATLAB case study, neural network of practical examples)

说明：  ：DBSCAN是一个基于密度的聚类算法。该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数 据库中发现任意形状的聚类。但DtLqCAN算法没有考虑非空间属性，且DBSCAN算法需扫描空间数据库中每个点的e一 邻域来寻找聚类，这使得DBSCAN算法的应用受到了一定的局限。文中提出了一种基于DBSCAN的算法，可以处理非空 间属性，同时又可以加快聚类的速度。(: DBSCAN is a density-based clustering algorithm. The algorithm has a sufficiently high density area is divided into clusters, and to be with the &quot noise&quot found in the spatial database clusters of arbitrary shape. But DtLqCAN algorithm did not consider non-spatial attributes, and spatial database DBSCAN algorithm to be scanned for each point e in the neighborhood to find a cluster, DBSCAN algorithm which makes the application subject to certain limitations. In this paper, an algorithm based on DBSCAN can handle the non-spatial attributes, can also speed up the clustering speed.)