Java-and-Maltab-Hybrid-Programming

利用MATLAB语言实现二维信号多尺度离散小波分解(Using MATLAB language to achieve two-dimensional discrete wavelet multi-scale decomposition of signals)

 利用fft()进行快速傅立叶变换，得到频谱，画出正弦函数及其频谱  找出频谱中使得Y轴取最大值时的估计频率记为ft  加入白噪声，绘出信噪比和均方误差的关系曲线 ( using fft () for fast Fourier transformation, spectrum, to draw the sine function and its spectrum  find the spectrum makes the Y-axis maximum value when the estimated frequency is denoted by ft  adding white noise, SNR plot and mean square error curve)

说明：  详细介绍matlab的函数工具及其使用方法(Detailed introduction matlab function tool and its use)

DTF - equation implementation2(DTF- equation implementation2)

神经网络,数字识别,水印程序,matlab 里面有关于matlab数字识别的多份代码及资料， (Neural network, digital identification, watermark program, matlab inside matlab figures on the number of identification code and information)

说明：  求解细线天线或细直导线的辐射或散射特性的矩量法分析论文(Solution of thin wire antennas or small straight wire radiation or scattering characteristics of the moment method analysis of papers)

这是一个KNN分类器的matlab函数（K近邻分类器）,可自由选择参数k(it s a KNN classifier program of the matlab ,you can chose the parameter k to conduct the classify procedure )

用matlab仿真多目标跟踪中的航迹关联融合的程序，(Matlab simulation of multi-target tracking with the track association fusion procedure)

统的联合概率数据关联算法(IPDA)是在密集杂波环境下的一种良好的多目标跟踪算法， 但它是针对单传感嚣对多目标跟踪的情况下使用，不能直接用于多传感器对多目标的跟踪。针对这 一问题，文中提出了一种适用于多传感器多目标跟踪的JPDA算法，它以极大似然估计完成对来自 多传感器的测量集合进行同源最优分划，然后采用JPDA方法对多目标进行跟踪。经过理论分析和 仿真试验，证明了该方法能有效地进行多传感器多目标的跟踪，且具有算法简单、跟踪精度高、附 加的计算量小等优点。(Abstract)m JointProbabilisticDataAssociation(JPDA)solves single sensormultitatgcttrackingin ClUtter,butitc锄not bc used directly in mnitisensor multitarget tracking．喇8 paper presents a method to implement multi—sensor multi—target tracking by combining maximum likelihood estimation wim JPDA The maximum Iikelihood estimation is used to classify the same source observations at one time into the same set,and血en JPDA implements multi—target uacking after the position fitsed．The theory analysis and computer simulation show that this algorithm may achieve multi—sensor multi—target tracking perfectly with low calculation load added and higher precision 。)

Sparse MRI Sparse MRI reconstruction based compressed sensing(Sparse MRI reconstruction based compressed sensing Sparse MRI reconstruction based compressed sensing)