资源列表
GPRmatlab
- GPR matlab The function should work with MATLAB v 5 and above. Please do not hesitate to contact me with any ideas for improving it or to point out any bugs that you find. -GPR Matlab The function should work with MA un v 5 and above. Please do no
w4
- 自己编写的用于消噪的维纳matlab程序，用了递推算法~-their preparation for the denoising Wiener Matlab program, a recursive algorithm ~
matsig-0.2.4
- 用于语音识别语音增强方面的matlab工具包，非常值得参考-for Speech Recognition speech enhancement of Matlab tool kit is very worthwhile reference! !
zhongzhilb
- 一个比较简单的中值滤波，程序比较短也比较容易懂，matlab编写-a relatively simple median filter, a relatively short procedure is relatively easy to understand, and the preparation of Matlab
BPclose
- bp 网络逼近函数,作正弦函数逼近.对初学者来说是不错的例子.-bp network approximation functions for sine function approximation. For beginners is a good example.
renyiweifen
- Duffing振子的Matlab程序，用于产生Duffing振子序列。-Duffing oscillator Matlab procedures used to produce Duffing oscillator sequence.
wavelet_basis_construction
- 此小程序用于构造小波基 并采用双尺度方程求解小波基函数-this small procedure for the construction of small Porgy and double standards equation wavelet function
wavelet_filter_construction_and_noise_elimination.
- 1 此函数用于研究Mallet算法及滤波器设计 2 此函数仅用于消噪-this function to a study Mallet filter design algorithms and 2 of this function is used only for Noise Cancellation
weimin
- 读取语音信号（用matlab的wavread指令），把语音信号分帧、加窗，进行清浊分割，提取基 频，这一部分较简单，自己编程序做。参考文献自己到图书馆期刊网上查找。 提取语音信号的lpc参数，可调用lpcfit.m 程序（我提供，见附件），将源、目标语音的浊音 段的lpc系数进行DTW规整，调用pathita2.m 程序（我提供，见附件）。将规整得到的lpc系数 转换成lsp参数，调用lpcar2ls.m 程序（我提供，见附件）， 再进行转换映射，调用matlab 的指令ne
lpcfit
- 提取语音信号的lpc参数可调用lpcfit.m 程序-voice signal from the lpc parameters of available procedures lpcfit.m
lms2dim3
- 分类线不过原点的2维两类不可分样本的分类分类线不过原点的2维两类可分样本的分类,还有些课件.-classification lines origin can not be two types of two-dimensional samples of the sub-classification classification line but the origin can be divided into two types of two-dimensional samples classific
LMS2dim2u
- LMS2dim2u：分类线过原点的2维两类不可分样本的分类-LMS2dim2u : classification of zero-crossing the line two hours, not two-dimensional sample separation