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张正友的有关三维重建的论文 值得三维重建研究人员好好学习研究(Zhang Zhengyou of the three-dimensional reconstruction of the paper Worthy of three-dimensional reconstruction of the researchers learn)

基于功率谱密度的平面十字阵列被动声定位matlab仿真程序(Based on planar cross power spectral density array of passive acoustic localization matlab simulation program)

贝叶斯估计方法的matlab程序,这是一个简单的例子,但很有用(Bayesian estimation methods matlab program, this is a simple example, but very useful)

非常详细的MUSIC谱估计程序，自己写的，毕业设计，保证结果正确且可以运行。有非常详细的注释，每句话都有注解，简明易懂，保证可以看懂并学到知识，并且每一步与MUSIC算法详细的对应和算法解释，不管是学习程序还是学习算法都很有帮助，.m文件中是程序的一部分，全部代码在WORD中，肯定是你见过的最好的代码(MUSIC spectrum estimation very detailed procedures for their own writing, graduation, there are very detailed notes, every word has a comment, simple to understand, to ensure you can read and acquire knowledge, and every step of the MUSIC algorithm and the corresponding detailed and algorithm explanation, whether the learning process or learning algorithms are very helpful)

核查的关键在于对核材料属性准确、有效地识别[1][2]。利用252Cf作为随机脉冲中子源，对其入射核材料所产生的诱发裂变中子脉冲信号进行采集、处理和分析，得到自相关、互相关、自/互功率谱、功率谱密度比等一系列参数，从而反演核材料内部的反应性的情况，便可用于分析和识别核材料，其基本原理就是252Cf中子源驱动噪声分析测量法[(The result shows that the trained Elman neural network is able to identify the characteristics of correlation function, to distinguish different concentrations, and the average recognition rate reaches 90 , with high robustness.)

说明：  这是个利用粒子群算法(PSO)优化PID控制器参数的matlab程序，其中选取的性能指标为ITAE。(this is the use of particle swarm algorithm (PSO) PID controller optimized parameters of Matlab procedures, these performance indicators selected for ITAE.)

MATLAB软件对不同发射天线、不同接收天线、不同信噪比下的MIMO系统容量进行仿真，得出在不增加带宽和天线发送功率的情况下利用MIMO信道成倍地提高无线信道容量(MATLAB software for different antennas, different antenna, different SNR of the MIMO system capacity for simulation, obtained without increasing the bandwidth and the antenna transmit power where the use of MIMO channels to improve wireless channel capacity multiplied)

用ica进行信号处理，能有效的分离出源信号(Ica with the signal processing, can efficiently separate the source signals)

image segmentation, level set gragh

unslotted model of sensor networks