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CepSpecPackage
- 无参数功率谱估计，基于matlab编程语言
图8-6-2随机信号不同取样长度时的功率谱估计0928f
- 随机信号不同取样长度时的功率谱估计，matlab实现，用于数字信号处理-random sampling signal different lengths of power spectral estimation, Matlab achieve for digital signal processing
memcof
- 最大熵法实现功率谱估计，内附算法实例及数据结果。-Maximum entropy power spectrum estimation method, containing the results of algorithm and data examples.
codes
- 基于累计量的奇异值－总体最小二乘法求AR参数 用奇异值－总体最小二乘法求AR参数 一般最小二乘法求AR参数 根据AR参数和自相关函数以及AR阶数用Cadzow谱估计子求出频谱密度-Based on the cumulative amount of singular value- total least squares method for AR parameter using singular value- total least squares method for AR parameter
d9000mpi3
- 对互谱法被动测距的原理及算法各个环节进行仿真验证：加权最小二乘估计中权系数的选取；相关窗长度的选取；各频段综合方法等等。最后实现了对9000m—15000m距离的测距-Cross-spectral method for passive ranging all aspects of theory and algorithms for simulation: weighted least squares estimation of the right of the selection coeffic
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
gcor
- 分数低阶协方差谱的MATLAB程序，含4种计算分数低阶协方差谱的估计方法-Fractional lower order covariance spectrum MATLAB program, including four kinds of calculation of fractional lower order covariance spectral estimation method
Burg
- 在MATLAB环境下，用Burg算法实现对随机信号的功率谱估计-Random signal of the power spectrum estimation with Burg algorithm in the MATLAB environment,
kannou_v41
- 通过反复训练模板能有较高的识别率，使用大量的有限元法求解偏微分方程，现代信号处理中谱估计在matlab中的使用。- Through repeated training ibGEjiBlate have higher recognition rate, Using a large number of finite element method to solve partial differential equations, Modern signal processing used in the
gensie
- matlab编写的元胞自动机，现代信号处理中谱估计在matlab中的使用，计算晶粒的生长，入门级别程序。- matlab prepared cellular automata, Modern signal processing used in the spectral estimation in matlab, Calculation of growth, entry-level program grain.
guifun
- 现代信号处理中谱估计在matlab中的使用，完整的图像处理课设，包含所有源代码，汽车图像，各种资源分配算法实现。- Modern signal processing used in the spectral estimation in matlab, Complete class-based image processing, contains all of the source code, auto image, Various resource allocation algorithm.
gingyui_v88
- MinkowskiMethod算法 ,重要参数的提取，现代信号处理中谱估计在matlab中的使用。- MinkowskiMethod algorithm, Extract important parameters, Modern signal processing used in the spectral estimation in matlab.
lansun_v32
- 现代信号处理中谱估计在matlab中的使用，已调制信号计算其普相关密度，D-S证据理论数据融合。- Modern signal processing used in the spectral estimation in matlab, Modulated signals to calculate its density Pu-related, D-S evidence theory data fusion.
lantui_v77
- 现代信号处理中谱估计在matlab中的使用，在matlab环境中自动识别连通区域的大小,计算加权加速度。- Modern signal processing used in the spectral estimation in matlab, Automatic identification in the matlab environment the size of the connected area, Weighted acceleration.
sanfen
- 验证可用，现代信号处理中谱估计在matlab中的使用，ML法能够很好的估计信号的信噪比。- Verification is available, Modern signal processing used in the spectral estimation in matlab, ML estimation method can be a good signal to noise ratio.
guilen_v11
- 现代信号处理中谱估计在matlab中的使用，汽车课设货车Matlab驱动力图程序，采用热核构造权重。- Modern signal processing used in the spectral estimation in matlab, Car class-based truck driver trying to Matlab program, Thermonuclear using weighting factor.
nougie_v14
- 利用最小二乘法进行拟合多元非线性方程，现代信号处理中谱估计在matlab中的使用，比较了软阈值，硬阈值及当今各种阈值计算方法。- Multivariate least squares fitting method of nonlinear equations, Modern signal processing used in the spectral estimation in matlab, Comparison of soft threshold and hard threshold and
faofei
- matlab小波分析程序，关于非线性离散系统辨识，现代信号处理中谱估计在matlab中的使用。- matlab wavelet analysis program, Nonlinear discrete system identification, Modern signal processing used in the spectral estimation in matlab.
qanqei_v23
- 是学习PCA特征提取的很好的学习资料，单径或多径瑞利衰落信道仿真，现代信号处理中谱估计在matlab中的使用。- Is a good learning materials to learn PCA feature extraction, Single path or multipath Rayleigh fading channel simulation, Modern signal processing used in the spectral estimation in matlab.
Desktop
- matlab经典法之周期图法对随机信号进行功率谱估计。(Matlab classical method of power spectrum estimation)