一种简单有效的基于动态时变语音识别源码 对于大多数研究者来说,寻找能够匹配二重时间序列信号的最佳途径是很重要的,因为它有许多重要的应用需求.DTW是实现这项工作的显著技术,尤其在语音识别技术领域,在这里一个测试信号被按照参照模板拉伸或压缩, ,Searching for the best path that matches two time-series signals is the main task for many researchers, because of its importa

C语言DTW算法实现,主要功能: 1)快速近邻DTW比较 2)算法稳定 3)节省内存-== Key features == 1) Fast Dynamic Time Warping nearest neighbor cost retrieval. 2) Persistence 3) External-memory: you need only a constant amount of RAM

C语言DTW算法实现,主要功能: 1)快速近邻DTW比较 2)算法稳定 3)节省内存-== Key features == 1) Fast Dynamic Time Warping nearest neighbor cost retrieval. 2) Persistence 3) External-memory: you need only a constant amount of RAM

NDtw ==== Dynamic Time Warping (DTW) algorithm implementation for .NET C# Features ==== * Single or multivariate * Data preprocessing options (none, centering, normalization, standardization) * Optional weights for variables