LMD分解程序 能有效解决EMD的模态混叠现象，LMD结合样本熵，里面有个例子(The LMD decomposition program can effectively solve the modal aliasing phenomenon of EMD. LMD combines with sample entropy, and there is an example)

多元经验模式分解（MEMD）算法是EMD算法从单个变量到任意数量的变量的扩展，其与经验模态分解一样存在模式混合问题，基于噪声辅助的多元经验模式分解（NAMEMD）就在对MEMD的改进，解决其问题。(The multiple empirical mode decomposition (MEMD) algorithm is an extension of the EMD algorithm from a single variable to any number of variables. Like

信号iceemdan模态分解，包含测试信号，简单易实现，需要自己安装emd工具箱((It can be used for signal EMD, EEMD, VMD decomposition. Because the algorithm adds its own annotations, it's easy to understand))