▍1. hh_fangcheng
H-H微分方程的matlab原代码,内包含说明文档,对模拟神经元有帮助.(H-H Differential Equations Matlab original code, which includes documentation, simulated neurons to help.)
H-H微分方程的matlab原代码,内包含说明文档,对模拟神经元有帮助.(H-H Differential Equations Matlab original code, which includes documentation, simulated neurons to help.)
关于希尔伯特黄频谱的计算程序,提取的频谱信息可用于语音识别、故障检测等。(on Hilbert Huang spectrum calculation procedures to extract information of the spectrum can be used for voice recognition, fault detection.)
基于熵的端点检测算法,比传统的端点检测能更精确的检测出端点(endpoint detection algorithm than the traditional endpoint detection more accurate detection of Endpoint)
基于LMS算法的变换域的源程序,里面给出了学习曲线,迭代后的输出曲线(LMS algorithm based on the Domain source, which is a learning curve, the output iterative curve)
关于lms经典算法汇总,包括lms,nlms,LMS_Equalizer,Basic_LMS,LMS toolbox等等。(classical algorithm for matrix lms, including lms, nlms. LMS_Equalizer, Basic_LMS, LMS toolbox, and so on.)
语音识别中的两种特征提取方法lpcc和mfcc,还有一个是文本无关的识别算法dtw,另外还有一个是预处理消噪部分的。共享一下,这些都是我调试过的,好用。(Speech Recognition two feature extraction methods and mfcc lpcc. There is a text-independent recognition algorithm dtw, in addition to a pretreatment is part of the noise source. Sharing that those are off the debugging and ease of use.)
FastICA算法,用于信号的独立分量分析,在ICA的基础上加快了收敛速度,有更高的效率!并且增加了图象界面,使用方便!(FastICA algorithm, the signal for an independent component analysis, at the ICA on the basis of accelerating the convergence rate, a more efficient! And to increase the image user interface!)
语音语谱图分析程序,提供了数字样本数据,值得参考.matlab程序.(language voice spectrum analysis procedures, and providing a digital sample data, a good reference. Matlab procedures.)
端点检测程序 多频带,熵 谱熵 teger能量 希望大家好好学习好好利用(endpoint detection procedures multiband, entropy spectral entropy teger energy hope that we learn to make good use)
一个基于小波变换的图像去噪声程序 仿真软件采用的是matlab(a Wavelet-Based Image noise process simulation software using the Matlab)
一个完整的基于Matlab的DTW模型算法及高效算法程序,能快速识别数字0-9,运行testdtw即可。(An excellent MATLAB program for the algorithm as a DTW model. It can recognise the number of 0-9. Try it, just run testdtw.)
cubica算法performes ICA by diagonalization of third- and fourth-order cumulants simultaneously(cubica algorithm performes ICA by diagonalization of third- and fourth-order cumulants simultaneously)