-
ding
选取windows系统自带的ding.wav信号作为分析对象，在Matlab软件平台下，利用函数wavread对音频信号进行采样，记住采样频率和采样点数，听一下原始声音sound(y, fs, bits)。
（2）音频信号的频谱分析，先画出音频信号的时域波形；然后对音频号进行快速傅里叶变换fft(y,N)，N取32768，画出信号的频谱特性，加深对频谱特性的理解。
（3）根据频谱，反演时域特性，画出时域波形。寻找幅值最大的两个频率，此频率除以fft点数在乘以采样频率就是信号的主频，即可合成信号的时域图形，听一下声音。
（4）对原音频信号进行1024点的分段付立业分析meshgrid
（5）根据主要频线合成音频，并画出时域图形，试听合成效果。
（6）采用线性插值（linspace）和傅立业反变换(fliplr, ifft)分别合成音频，并画出时域图形，试听效果。
(err)
- 2009-01-13 16:23:47下载
- 积分：1
-
Demo1
Demo of Level set project
- 2009-03-26 14:58:52下载
- 积分：1
-
matlab7
一些关于matlab7的实用教程，对于初学者很有帮助，希望能帮你快速入门(matlab)
- 2010-05-14 17:04:22下载
- 积分：1
-
ESSAI4
9 BUS SIMPOWERSYSTEMS MODEL
- 2014-01-09 08:15:58下载
- 积分：1
-
CEEMD_V
ceemdan是对EMD EEMD的改进算法，此程序包中有子程序和测试例子，可以运行(his algorithm was presented at ICASSP 2011, Prague, Czech Republic
Plese, if you use this code in your work, please cite the paper where the
algorithm was first presented.
If you use this code, please cite:
M.E.TORRES, M.A. COLOMINAS, G. SCHLOTTHAUER, P. FLANDRIN,
"A complete Ensemble Empirical Mode decomposition with adaptive noise,"
IEEE Int. Conf. on Acoust., Speech and Signal Proc. ICASSP-11, pp. 4144-4147, Prague (CZ))
- 2014-06-28 09:35:47下载
- 积分：1
-
MCMC
这是马尔可夫-蒙特卡罗算法的MATLAB源程序.(This is the Markov- Monte Carlo algorithm for MATLAB source code.)
- 2008-03-20 17:11:06下载
- 积分：1
-
20091206_High_sensor
采用matlab/simulink仿真环境建立捷联惯导系统的垂向通道仿真模型，利用高度气压计进行增稳仿真，取得良好的高度通道稳定的效果。(The model of vertial channel was developed in matlab/simulink.By using the high sensor to upgrade the high stability.)
- 2010-01-04 12:19:08下载
- 积分：1
-
wienerfilter2
基于维纳滤波器算法,对加噪信号进行滤波.(Wiener filter algorithm based on the increase in noise signal filtering.)
- 2007-01-17 00:48:19下载
- 积分：1
-
automatic-Emotion-predictor-sytem
A working setup that focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into
arousal, expectation, intensity, power and valence level of the observed
subject as there has been virtually no research bearing on this topic.
Preliminary experiments show that it is possible to automatically predict
emotions in terms of these five dimensions (arousal, expectation, intensity,
power and valence) from conversational head gestures. Dimensional
and continuous emotion prediction from spontaneous head gestures has
been integrated in the SEMAINE project [
- 2013-11-26 22:40:05下载
- 积分：1
-
shixufenxi-2
基于时序分析的变形监测数据处理基于时序分析的变形监测数据处理基于时序分析的变形监测数据处理(Deformation monitoring data processing based on time series analysis of deformation monitoring data processing based on time series analysis of deformation monitoring data processing based on timing analysis)
- 2012-11-23 16:28:00下载
- 积分：1
