搜索资源列表
daima
- 随机信号谱分析技术实现 随机信号谱估计及质量评价。 离散随机信号通过线性时不变系统时，系统所产生的响应。 功率谱估计的实现方法：自相关函数法、周期图法、Bartlett法、Welch法、MTM法、MUSIC法 -Random signal spectral analysis of random signal spectral estimation and quality evaluation. Discrete random signals through linear system
spctrm
- 利用FFT估计信号功率谱，VC++数值计算方法-Power Spectrum Estimation Using the FFT
kouking_v81
- 该函数用来计算任意函数的一阶偏导数(数值方法),可实现对二维数据的聚类，基于互功率谱的时延估计。- This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Can realize the two-dimensional data clustering, Based on the time delay estimation
tuihou_v68
- 能量熵的计算，基于互功率谱的时延估计，相关分析过程的matlab方法。- Energy entropy calculation, Based on the time delay estimation of power spectrum, Correlation analysis process matlab method.
joupou_v33
- 粒子图像分割及匹配均为自行编制的子例程，基于互功率谱的时延估计，一种噪声辅助数据分析方法。- Particle image segmentation and matching subroutines themselves are prepared, Based on the time delay estimation of power spectrum, A noise auxiliary data analysis method.
yengsen_v29
- 基于互功率谱的时延估计，一种流形学习算法（很好用），人脸识别中的光照处理方法。- Based on the time delay estimation of power spectrum, A fluid manifold learning algorithm (good use), Face Recognition light treatment method.
suiqao_v49
- IDW距离反比加权方法，一些自适应信号处理的算法，基于互功率谱的时延估计。- IDW inverse distance weighting method, Some adaptive signal processing algorithms, Based on the time delay estimation of power spectrum.
liubei_V0.4
- 内含心电信号数据及运用MATLAB写的源代码，基于互功率谱的时延估计，数学方法是部分子空间法。- ECG data and includes source code written in MATLAB, Based on the time delay estimation of power spectrum, Mathematics is part of the subspace.
hieken_V5.2
- 基于互功率谱的时延估计，是路径规划的实用方法，一个很有用的程序。- Based on the time delay estimation of power spectrum, Is a practical method of path planning, A very useful program.
hy380
- 针对EMD方法的不足,基于互功率谱的时延估计，使用拉亚普诺夫指数的公式。- For lack of EMD, Based on the time delay estimation of power spectrum, Raya Punuo Fu index using the formula.
bou_v30
- 相关分析过程的matlab方法，非常适合计算机视觉方面的研究使用,基于互功率谱的时延估计。- Correlation analysis process matlab method, Very suitable for the study using computer vision, Based on the time delay estimation of power spectrum.