suptitle

Matlab code. My friend give this to me. I hope it will be helpful to others.

matlab图像处理命令的解释和实例 (matlab image processing command explanation and examples)

说明：  神经网络与matlab7的实现 配套资料下载 .m格式(neural network and the realization matlab7 supporting information downloaded. M format)

这是一个基于小波的数字音频程序。对于最近做毕业设计的同学有帮助。 (This is a wavelet-based digital audio programs. For students recently graduated design.)

VMD方法是在传统维纳滤波的基础上，提出的一种非递归自适应信号分解新方法。与EMD方法和LMD方法相比，VMD方法分解的信号，具有精度高、收敛快和鲁棒性好等特点，适用于处理滚动轴承故障信号。(The VMD method is a new non recursive adaptive signal decomposition method based on traditional Wiener filtering. Compared with the EMD method and the LMD method, the signal decomposed by the VMD method has the characteristics of high precision, fast convergence and good robustness. It is suitable for handling the fault signal of rolling bearing.)

功能描述： 小数延迟FIR滤波器，对参考阵元信号signal_ref进行 length(tau) M次延迟，分别得到M个阵元的采样信号 关键问题： 若τ 1.2Ts,则Delay(i) 2,tau_valid(i) 0.2Ts 若τ 0.6Ts,则Delay(i) 1，tau_valid(i) -0.4Ts 当tau_valid(i)>0或<0时，从卷积后的数据y_FIR_delay中取值启示位置不同 函数能够实现输入任意延时tau，输出信号波形与理想波形之间误差很小。( Description: fractional delay FIR filter array element of a reference signal signal_ref performed length (tau) M delay times, respectively, to obtain a sample signal array element M key question: if τ 1.2Ts, then Delay (i ) 2, tau_valid (i) 0.2Ts if τ 0.6Ts, then Delay (i) 1, tau_valid (i) - 0.4Ts when tau_valid (i)> 0 or < 0, the volume data y_FIR_delay product after the Enlightenment values at different positions function can be realized enter any delay error between tau, the output signal waveform and the ideal waveform is small.)

Function to plot bar graphics in matlab

基于小波变换的红外图像与可见光图像的融合，2级小波变换，多种融合规则(Based on wavelet transform infrared image and visible image fusion, two wavelet transform, a variety of fusion rules)

OFDM系统中信道估计基于LS改进算法--基于DFT的信道估计算法实现(LS channel estimation in OFDM system based on the improved algorithm based on DFT channel estimation algorithm )

说明：  可计算序列的信息熵、两个序列间的联合信息熵和互信息(This file can calculate the entropy, joint entropy and mutual information)