qitijiancechengxu

用自适应门限的方法进行跳频信号的参数估计，取得了较好的效果(Adaptive threshold method estimates the parameters of frequency hopping signals, achieved good results)

可直接运行的基于拉普拉斯以及小波变换的多种融合方法的代码(Can be run directly based on the Laplace and the wavelet transform multiple fusion method code)

详细的写出来STBC在MATLAB中的应用(Write out in detail in the application of STBC in MATLAB)

用MATLAB实现数值分析的不同计算方法的实现过程，是研究生一年级需要的(Numerical Analysis Using MATLAB to achieve the realization of a different method of calculation process is required first-year graduate students)

jordan canonical form of a nxn matris

为了弥补传统中值滤波器在进行图像降噪处理中的不足,在图像降噪技术中应用了自适应中值滤波器。文中重点介绍了自适应中值滤波器的工作原理并在Matlab平台上进行了仿真试验，与传统中值滤波器进行了比较,计算机仿真结果表明在对密度较大的椒盐噪声进行滤波时,自适应中值滤波较传统中值滤波具有较大的优越性。(To remedy disadvantage of traditional median filtering algorithms in image denoise ,adaptive median filter is introduced and applied to image denoise. Key technology in actual uses is analyzed and is implemented in Matlab platform.Compared with traditional median filter , the computer simulation results show that when used to filter image with the higher level of noise , adaptive median filter is preferable to traditional median filter.)

This paper focuses on the analysis of Electromagnetic Interference Problem associated with the resonant converters because it affects their Electro Magnetic Compatibility (EMC). The principle of Electromagnetic Compatibility (EMC) is to allow a correct and optimum functioning of any electrical or electronic devices in the presence of each other. In other words, it is the right of electrical/electronic equipment to co-exist in an electromagnetic environment without disturbing each other.

已知质量流量，热流密度和饱和温度等参数，可用Mahmoud等人换热关联式进行非线性拟合(If the mass flow, heat flux and saturation temperature parameters are known,the correlation of Mahmoud et al. can be used to perform nonlinear fitting)

Reduce noise in Binary Image 二值图去噪小程序，matlab(Reduce noise in Binary Image binary image denoising applet, matlab)

主要叙述在matlab环境下熟悉对svm的操作以及svm的主要特性包括分类和回归(The main narrative in the matlab environment familiar with the operation of the SVM and the main features include SVM classification and regression)