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Description: jaccobi迭代法和GS迭代法求解线性方程组，并有著名病态对称正定矩阵Hilbert矩阵的生成程序和其不同维数下，求解结果的对比作图-jaccobi iteration and GS iterative method for solving linear equations, and a well-known pathological symmetric positive definite matrix Hilbert matrix formation process and the different dimension, the results of the solution Comparative mapping
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Size: 13298 |
Author: 高兵 |
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Description: SOR（超松弛）迭代发求解线性方程组问题，带有Hilbert矩阵生成程序和其不同维数下求解的结果对比作图-SOR (Overrelaxation) iteration made for solving linear equations, with Hilbert matrix formation process and the different dimensions of the results evaluated Comparative mapping
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Size: 12936 |
Author: 高兵 |
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Description: jaccobi迭代法和GS迭代法求解线性方程组，并有著名病态对称正定矩阵Hilbert矩阵的生成程序和其不同维数下，求解结果的对比作图-jaccobi iteration and GS iterative method for solving linear equations, and a well-known pathological symmetric positive definite matrix Hilbert matrix formation process and the different dimension, the results of the solution Comparative mapping
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Size: 13312 |
Author: 高兵 |
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Description: SOR（超松弛）迭代发求解线性方程组问题，带有Hilbert矩阵生成程序和其不同维数下求解的结果对比作图-SOR (Overrelaxation) iteration made for solving linear equations, with Hilbert matrix formation process and the different dimensions of the results evaluated Comparative mapping
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Size: 12288 |
Author: 高兵 |
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Description: HHT变换的核心是EMD，在此项过程中通过EMD的编程和HHT的编程来实现了希尔伯特黄变换。可以看出处理此方法用来处理非线性信号为更好的方法。 -HHT Transform is the core of EMD, in the process of programming through EMD and HHT programming to achieve the Hilbert Huang Transform. As can be seen this method used to deal with non-linear signal processing for better alternatives.
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Size: 2048 |
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Description: 希尔伯特—黄变换的控制台程序，里面用到了线性插值，结果以磁盘文件形式输出-Hilbert- Huang Transform the console program, which used a linear interpolation, resulting in the form of the output to disk file
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Size: 3072 |
Author: hailun |
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Description: ex5_1 I-型线性相位FIR滤波器
ex5_2 II-型线性相位FIR滤波器
ex5_3 III-型线性相位FIR滤波器
ex5_4 IV-型线性相位FIR滤波器
ex5_5 矩形窗频响
ex5_6 希尔伯特变换器设计－汉宁窗
ex5_7 低通滤波器设计－汉明窗
ex5_8 带通滤波器设计－布莱克曼窗
ex5_9 低通滤波器设计－凯塞窗
ex5_11 频率采样技术：低通，朴素法
ex5_12 频率采样技术：低通, 最优法T1 & T2
ex5_13 频率采样技术：带通, 最优法T1 & T2
ex5_14 频率采样技术：高通, 最优法T1
ex5_15 频率采样技术：差分器
ex5_16 频率采样技术： 希尔伯特变换器
ex5_17 利用Parks-McClella算法设计低通滤波器
ex5_18 用PM算法进行的带通滤波器设计
ex5_19 用PM算法进行的高通滤波器设计
ex5_20 用PM算法进行的阶梯滤波器设计
ex5_21 用PM算法进行的差分器设计
ex5_22 用PM算法进行的希尔伯特变换器设计-ex5_1 I-type linear phase FIR filter
ex5_2 II-type linear phase FIR filter
ex5_3 III-type linear phase FIR filter
ex5_4 IV-type linear phase FIR filter
rectangular window frequency response ex5_5
Hilbert ex5_6 converter design- Hanning window
low-pass filter design ex5_7- Hamming window
ex5_8 bandpass filter design- Blackman window
ex5_9 low-pass filter design- Kaiser window
ex5_11 sampling frequency: low-pass, a simple method
ex5_12 sampling frequency: low-pass, optimal method T1 & T2
sampling frequency ex5_13: band-pass, optimal method T1 & T2
ex5_14 sampling frequency: high-pass, optimal method T1
sampling frequency ex5_15: differentiator
sampling frequency ex5_16: Hilbert converter
Parks-McClella use ex5_17 algorithm design low-pass filter
PM algorithm ex5_18 with the band-pass filter design
PM algorithm ex5_19 with the high-pass filter design
PM algorithm used ex5_20 ladder filter design
PM algorithm used ex5_21 differential design
PM al
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Size: 4096 |
Author: 张满超 |
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Description: SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code.
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Size: 117760 |
Author: 秀 |
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Description: Kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping.
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Size: 2048 |
Author: Karthikeyan |
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Description: Kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping.-Kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non-linear mapping.
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Size: 3072 |
Author: rem |
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Description: 针对传统线性调频(LFM)信号参数估计算法中复杂的搜索和计算问题，提出了一种不需要参数搜索的快速
LFM信号参数估计算法。该算法先用希尔伯特变换估计LFM信号瞬时相位，再用二次相位函数拟合LFM信号瞬
时相位从而得到初始频率和调频斜率的估计-The traditional linear frequency modulation (LFM) signal parameter estimation algorithms and computational complexity of the search problem, we propose a fast search without LFM signal parameter estimation algorithm. The algorithm first estimated with the Hilbert transform of LFM signal instantaneous phase, and then the second phase of LFM signal instantaneous phase function fitting to obtain the initial estimates of the frequency and chirp rate
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Size: 276480 |
Author: uncle Wang |
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Description: The Hilbert transform is a linear operator which takes a function, u(t), and produces a function, H(u)(t), with the same domain.
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Size: 1024 |
Author: amitriptilin |
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Description: SVM方法是通过一个非线性映射p，把样本空间映射到一个高维乃至无穷维的特征空间中(Hilbert空间)，使得在原来的样本空间中非线性可分的问题转化为在特征空间中的线性可分的问题．这是一本介绍SVM方法的应为资料-SVM method is a non-linear mapping p, the sample space is mapped into a high-dimensional and even infinite dimensional feature space (Hilbert space), making the non-linear separable in the original sample space into the feature space in the linearly separable problem. This is an on SVM method data
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Size: 427008 |
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Description: 该程序用于Hilbert谱分解，可分析非平稳和非线的信号-The procedures used for the Hilbert spectral decomposition and analysis of non-stationary and non-linear signal
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Size: 510976 |
Author: 王伟 |
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Description: 解决一般的线性方程组，其中包含希尔伯特消元法和高斯隐式消元法两种方法。-Solve a generally linear equations, which contains two methods in Hilbert elimination method and Gauss implicit elimination method.
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Size: 109568 |
Author: 李鹏程 |
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Description: 一般方法求希尔伯特矩阵的对应的线性方程组的解法，并探讨其准确性-General method for solving Hilbert matrix corresponding to the solution of linear equations, and to investigate the accuracy
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Size: 242688 |
Author: maxwellddd |
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Description: Hilbert-Huang变换之EMD分解程序。可以直接运行，以及附有几个详细例子。可以用以对非线性非平稳信号的处理，效果理想。-Hilbert-Huang transform EMD decomposition process. Can be run directly, as well as with several detailed examples. Can be used for non-linear non-stationary signal processing, the results are satisfactory.
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Size: 8192 |
Author: 鹏love敏 |
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Description: This program designs four types of linear phase finite impulse response filters.(1) Equiripple Linear Phase Filter (multiple passbands and stopbands).(2) Equiripple Linear Phase Filter (multiple passbands and stopbands). (3) Equiripple Differentiator (4)Equiripple Hilbert Transform Filter.-This program designs four types of linear phase finite impulse response filters.(1) Equiripple Linear Phase Filter (multiple passbands and stopbands).(2) Equiripple Linear Phase Filter (multiple passbands and stopbands). (3) Equiripple Differentiator (4)Equiripple Hilbert Transform Filter.
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Size: 287744 |
Author: lovedeep |
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Description: Hilbert矩阵病态线性代数方程组的求解 matlab 代做 代写-Hilbert matrix is ill-conditioned linear algebraic equations matlab doing some ghostwriting
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Size: 31744 |
Author: 李雷 |
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Description: HHT是HuangE等提出的新的信号处理方法，适用于非线性非平稳的信号分析，被认为是近年来对以傅立叶变换为基础的线性和稳态谱分析的一个重大突破。-The new signal processing method, proposed by Huang E et al., is suitable for nonlinear and non-stationary signal analysis, which is considered as a major breakthrough in the linear and steady-state spectral analysis based on Fourier transform in recent years.
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Size: 6538240 |
Author: 叶华迅 |
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