li4

贝叶斯分类器的分类原理是通过某对象的先验概率，本文详细介绍贝叶斯分类器，使用贝叶斯分类器对样本进行训练分类，得到良好分类结果，并对分类结果进行分析。(Principle of Bayesian classifiers is through prior probability of an object, the paper describes Bayesian classifier, Bayesian classifier using the training sample classification, the classification results are good, and the classification results were analyzed.)

~~~~~~~为初级学者使用的遗传算法~~~~~~~~~~~~(Genetic Algorithms for Primary learner)

fiber optic gyroscope Allan variance and kalman filter matlab program

雷达课程的作业，在了解雷达原理后，对实际过程的仿真，有Chirp的形成，匹配滤波器，MTI，MTD的具体实现(Concrete realization of radar courses operating in the understanding of the radar principle, the simulation of the actual process, the formation of the Chirp matched filter, MTI, MTD)

地震资料处理，时频分析里的wiggle变换(Seismic data processing, time-frequency analysis in the transform wiggle)

Summary: The MPEG converter takes a MATLAB movie matrix and writes the movie to disk as an MPEG file. MATLAB Release: R12 Description: MPEG is an ISO standard movie encoding format. The MPEG converter for MATLAB takes a MATLAB movie matrix and writes the movie to disk as an MPEG file with file extension .mpg (MPGWRITE). It also takes an MPEG file and converts it into a MATLAB movie matrix (MPGREAD). (Summary: The MPEG converter takes a MATLAB movie matrix and writes the movie to disk as an MPEG file. MATLAB Release: R12 Description: MPEG is an ISO standard movie encoding format. The MPEG converter for MATLAB takes a MATLAB movie matrix and writes the movie to disk as an MPEG file with file extension. mpg (MPGWRITE). It also takes an MPEG file and converts it into a MATLAB movie matrix (MPGREAD).)

雷达中频回波仿真，对脉内起伏进行仿真，含脉内慢起伏和脉内快起伏(Radar IF echo simulation, simulation intrapulse downs, including slow downs and pulse-pulse fluctuations within the fast)

一种基于chan算法的tdoa定定位的gdop程序源码 (Given the positioning gdop program source code algorithm TDOA based chan)

这两本教材是关于MATLAB的,内容非常丰富,即适合初学者,也适合高手继续学习,是难的的好教材.希望对大家学习有帮助(those two books is about matlab.)

用于建模数据分集。计算各样本点的欧式距离，首先将距离最大的两个点放入第一个样本集，接着将余下距离最大的两个点放入第二个样本集，依次计算，将剩余数据点分别放入上述两个样本集。( This algorithm starts by selecting the two points furthest from each other (euclidean distance) and puts them both in a first set. Then the next two points furthest from each other are put in a second set, and the procedure is continued by alternatively placing pairs of points in the first or second set. For calibration applications, the second set can be the test set, and the calibration would be the concatenation of the first set plus the remaining samples.)