A fast Fourier transform (FFT) is an algorithm to compute the discrete Fourier transform (DFT) and its inverse. A Fourier transform converts time (or space) to frequency and vice versa an FFT rapidly computes such transformations. As a result, fast F

基于Matlab的语音识别系统，实现了基本的算法，具有较高的参考价值。-Matlab-based speech recognition system to achieve the basic algorithm, has a high reference value.

K-MEANS以及层次聚类算法 只要加入到工程就好使了 基本的聚类算法-K-MEANS and added to the hierarchical clustering algorithm works just fine so long as the basic clustering algorithm

该算法基本思想是利用一组带有相应权值的随机样本即粒子去逼近PHD分布和基数分布，其意义在于不仅解决重积分计算没有闭式解的难题，而且在滤波过程中，PHD函数被一系列离散的带权值的样本近似，随着样本粒子数量的增加，PHDF接近于Bayes最优估计，而且不受模型线性和高斯假设的限制，可以适用于非线性非高斯的随机系统。-The algorithm the basic idea is to use a set of random sample with the corresponding weight n