neighbor

地震资料 数据处理 分频去噪 模块 主要压制随机噪音 异常振幅 野值 大值 方法特点：1 针对性强，主要去除随机噪音；2 随机噪音识别能力强，达到了较高的去噪水平；3 具有自适应性，能根据不同位置的不同特点统计识别噪音；4 振幅保真，对有效信号的保护性好；5 操作者可根据经验选择参数组合灵活去噪，达到较好的结果。 应用对比：为了展示本模块的去噪效果，所选取的对比对象是某知名成熟商业软件的分频去噪模块，其去噪效果在当前诸多成熟软件模块中是佼佼者，在地震资料处理界具有很好的口碑。 通过对比，说明本模块：1 针对性强，主要去除随机噪音和异常振幅等。2 随机噪音识别能力强，达到了较高的去噪水平。3 具有自适应性，能根据不同位置的不同特点统计识别噪音。4 振幅保真，对有效信号的保护性好。5 操作者可根据经验选择参数组合灵活去噪，达到较好的结果。(Frequency-dependent noise attenuation seismic data, processing module, is mainly to suppress random noise, denoising abnormal/large amplitude values Method of characteristics: 1 targeted, mainly to remove random noise 2 random noise and strong ability to identify , reach a higher level of de-noising 3 is adaptive , able to identify the noise statistics according to the different characteristics of different positions 4 amplitude fidelity , the effective protection of the signal is good 5 denoising operator flexibility to select the combination of parameters according to the experience , to achieve better results . Application contrast: To demonstrate the effect of the de-noising module , the selected object is a well-known comparative commercial software divide mature noising module de-noising effect is the current leader in many mature software module in seismic data processing industry has a good reputation. By contrast, the description of the module : a targeted, mai)

说明：  打包做好界面的GS算法程序，欢迎大家借鉴(Packing the GS algorithm program of the interface, we welcome you to learn from it.)

该源代码是模式识别课程作业。通过K平均算法实现聚类的目的。效果比较好。另外本人还设计了等高线法，用于聚类，思想较好，效果一般，但是值得参考。(This code is a Pattern Recognition homework. It use Kmeans to clustering, and get a good result. It s good for a reference.)

动态矩阵控制 列车跟踪速度80KM/H 模型预测控制(DMC DMC)

在求混沌参数中所需要用到的GP算法，求关联维数的程序。(Seeking chaotic parameter needed GP algorithm, find the correlation dimension of the program.)

2015国赛A题太阳影子定位全国二等奖程序源码(A 2015 national title game sun shadow geopositioning second prize Open Source)

卡尔曼滤波 现代滤波器的实现,matlab源码(Kalman filter to achieve a modern filter, matlab source)

车牌定位原代码，具有较好的定位功能，实时性较好(License plate location of the original code, and has good positioning capabilities, better real-time)

To find and estimate of the best solution and parameter in our problem we can use the evolutionary programming. PSO (particle swarm optimization) is an applicable method to catch this target. In these files I show the Simple PSO that it can be base of solve complicated problem, the code could run by MATLAB.

基于JADE算法的Matlab数字水印技术(Based on the the JADE algorithm of Matlab digital watermarking technology)