WSNWnetworkmatlabvariable

说明：  车牌识别技术422 10.1 系统简介422 10.1.1 车牌定位技术综述423 10.1.2 车牌字符 识别技术综述423 10.2 车牌图像定位与分割算法424 10.2.1 车牌图像的(Vehicle Identification Technology System 422 10.1 422 10.1.1 plates positioning technology on 423 10.1.2 License Plate Recognition Technology 423 10.2 plates positioning and image segmentation algorithm 424 10.2.1 license plate image)

关于恶意代码检测和LTE网络，4G的LTE-A网络的外语文章(Foreign-language article about malicious code detection and lte network, lte-a network of 4g)

基于matlab的声音信号采集，分析处理，包括声卡采集，及浏览系统文件(Based on matlab voice signal acquisition, analysis and processing, including card acquisition, and browse system files)

bi-unipolar.m 1. Data 2. mod 3. AWGN 4. demod 5. Detect

按照幅度差法将时间序列映射成为复杂网络 计算出度以及入度(In accordance with the magnitude of the difference time series maps calculated well into a complex network)

说明：  常用方差分析方法，有单因素一元，多因素等(Common anOVA methods include single factor, single factor, multiple factor, etc)

介绍学习线性调频信号，包括在雷达应用中的匹配滤波（脉冲压缩）(The learning of linear FM signals, including applications in radar matched filtering (pulse compression))

实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。 对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。 深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。 利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。 (SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.)

用勒让德伪谱法，求解最优控制问题的DIDO工具箱。demo版本。license需要在其网站上填一个调查问卷(Legendre pseudospectral method for solving the optimal control problem DIDO toolbox. The demo version. license need to fill in a questionnaire on its website)

自己的一个实验,验证频率的采样定理.即采样点数要足够大.(own an experiment to test frequency of the sampling theorem. That sampling points should be powerful enough.)