LCRampFilter

seismic moment calculation

The fusion of high-spectral/low-spatial resolution multispectral and low-spectral/high-spatial resolution panchromatic satellite images is a very useful technique in various applications of remote sensing. Recently, some studies showed that a wavelet-based image fusion method provides high quality spectral content in fused images. However, most wavelet-based methods yield fused results with spatial resolution that is less than that obtained via the Brovey, IHS, and PCA fusion methods. In this paper, we introduce a new method based on a curvelet transform, which represents edges better than wavelets. Since edges play a fundamental role in image representation, one effective means to enhance spatial resolution is to enhance the edges. The curvelet-based image fusion method provides richer information in the spatial and spectral domains simultaneously. We performed Landsat ETM+ image fusion and found that the proposed method provides optimum fusion results.

卡尔曼滤波器的仿真模型图，非常好用，大家可以试一试(Simulation Model Chart of Kalman Filter)

说明：  应用电导增量法，实现光伏电池最大功率跟踪。(Achieve maximum power tracking of photovoltaic cells)

利用kalman实现目标跟踪的MATLAB源代码，能够实现。(Target tracking using kalman the MATLAB source code, can be achieved.)

matlab的命令大全，很详细，对各个命令的解释很全面，附带有例子(matlab command Daquan, very detailed, very comprehensive explanation of each command, with the example of)

fft源代码,感觉代码不错，所以传上去了，希望对大家有帮助。(fft source code, can only pass one, so this is only passing on part of the other part of the horse uploaded in the past)

Circuit Analysis I with MATLAB Computing and Simulink - SimPowerSystems Modeling Mar 2009

轨迹发生器,自动生成导航轨迹,可用于导航解算。(Trajectory generator, automatically generate the navigation path can be used in navigation solution)

基于小波变换神经网络的车流量预测，含程序和数据。小波分析是针对傅里叶变换的不足发展来的，傅里叶变换是信号处理领域中应用最广泛的的一种分析手段，然而它有一个严重不足，就是在变换是抛弃了时间信息，变换结果无法判断某个信号发生的时间，即傅里叶变化在时域中没有分辨能力。小波是一种长度有限，平均值为0的波形，它的特点包括：（1）时域都具有紧支集或近似紧支集；（2）直流分量为零。小波函数是由一个母小波函数经过平移与尺寸伸缩得到，小波分析即把信号分解成一系列小波函数的叠加。(Vehicle flow prediction based on wavelet transform neural network)