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Ch1899
小波变换在语音和生物医学信号处理中的应用 431
17.1 小波变换在语音信号处理中的应用 431
17.1.1 小波变换在语音增强中的应用 431
17.1.2 小波变换在语音压缩中的应用 433
17.2 小波变换在生物医学信号处理中的应用 435
17.2.1 基于小波变换的ECG信号压缩 435
17.2.2 基于小波变换的EEG信号多分辨率分析 437(wavelet transform voice, and biomedical signal processing of 431 in 17.1 wavelet transform voice signal Treatment of 431 17.1.1 wavelet transform in the speech enhancement of 431 17.1.2 wavelet change for the speech compression of 433 17.2 wavelet transform in biomedical signal processing applications 435 17. 2.1 Based on wavelet transform 435 ECG signal compression based on wavelet transform 17.2.2 EEG signal more hours Analysis of 437 identified)
- 2007-03-27 18:48:28下载
- 积分：1
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EEI
this is script for running Extended Elastic Impedance(EEI),from well log data
- 2011-07-17 19:46:47下载
- 积分：1
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MKD-SRC
matlab的MKD-SRC。多特征点的稀疏表示识别.(matlab the MKD-SRC.)
- 2014-03-17 15:53:33下载
- 积分：1
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yasuo
图像编码与压缩是数字信息时代的重要工具，在日常生活中都有广泛应用。该程序以matlab为平台，实现图像的压缩与融合。(Image coding and compression of digital information age is an important tool in their daily lives are widely used. Matlab in the program as a platform to achieve image compression and integration.)
- 2009-04-24 17:59:49下载
- 积分：1
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matlab
这是一个关于matlab的图形教程 (This is a tutorial on matlab graphics)
- 2008-05-18 05:18:13下载
- 积分：1
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ML_and_MAP
最大似然（ML）准则和最大后验概率（MAP）准则Matlab仿真(Maximum Likelihood (ML) criteria and maximum a posteriori probability (MAP) criteria Matlab simulation )
- 2011-05-31 15:45:22下载
- 积分：1
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keys
piono code by using matlab
- 2012-05-26 19:46:18下载
- 积分：1
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Lax-Wendrof
Lax-Wendrof法求解一介波动方程，初始条件c=1m/s, x=1-2,u=2m/s(Lax-Wendrof method to solve wave equation)
- 2014-11-29 07:04:21下载
- 积分：1
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00929583
for master degree seminar good file from ieee site
- 2013-10-04 18:24:00下载
- 积分：1
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BFGS
拟牛顿法和最速下降法(Steepest Descent Methods)一样只要求每一步迭代时知道目标函数的梯度。通过测量梯度的变化，构造一个目标函数的模型使之足以产生超线性收敛性。这类方法大大优于最速下降法，尤其对于困难的问题。另外，因为拟牛顿法不需要二阶导数的信息，所以有时比牛顿法(Newton s Method)更为有效。如今，优化软件中包含了大量的拟牛顿算法用来解决无约束，约束，和大规模的优化问题。(The quasi-Newton method and the Steepest Descent Methods only require that each step iterations know the gradient of the objective function. By measuring the change of the gradient, constructing a model of the objective function is sufficient to produce superlinear convergence. This method is much better than the steepest descent method, especially for difficult problems. In addition, because the quasi-Newton method does not require information on the second derivative, it is sometimes more effective than the Newton s Method. Today, the optimization software contains a large number of quasi-Newton algorithm used to solve the unconstrained, constraint, and large-scale optimization problems.)
- 2017-05-05 10:28:29下载
- 积分：1
