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Description:
谐波恢复的ARMA建模算法(基于SVD-TLS)（张贤达《现代信号处理》）。当谐波信号为复谐波的时，该算法仍然适用。但该程序中没有给出具体的实现。
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Size: 1553 |
Author: 罗万团 |
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Description: SVD-TLS
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Size: 15114 |
Author: battleq2q |
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Description: 矩阵的奇异值分解算法-A algorithm of matrix singular value decomposition
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Size: 9216 |
Author: 董启文 |
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Description: 巧妙的运用matlab控件自编程序！很有意思哦！在信号分析领域用途广泛！-clever use of Matlab self control procedures! Very interesting! In the field of signal analysis of a wide range of uses!
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Size: 1024 |
Author: Wendy |
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Description: DotNet版的线性方程的解法，包括：高斯消元法，用于n阶非奇异矩阵；SVD分解法，求最小二乘解.目前还很难找到免费的DotNet版的数值计算程序．这里有源码（J#)和dll文件．-Kind version of the linear equation solution, including : Gaussian Elimination Act, for order n nonsingular matrix; SVD decomposition method, least squares solution seeking. It is hard to find a free version of its Kind numerical calculation procedures. Here source (J#) and dll file.
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Size: 3072 |
Author: 凃道 |
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Description: 利用一般最小二乘法和SVD-TLS方法
进行AR参数估计和正弦波频率估计
-use of general and the least-squares method SVD-TLS AR method parameter estimates and the estimated frequency sine wave
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Size: 10240 |
Author: 梁心 |
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Description: SVD的有关资料，主要是入门的说明的，适合初学者。-SVD of the relevant information, the main entry of note is suitable for beginners.
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Size: 450560 |
Author: 蔡荣太 |
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Description: 由c语言编写的解非线性方程，线性方程组代码，包括LSQR,SIRT,SVD等算法源代码-By c language solution of nonlinear equations, linear equations code, including LSQR, SIRT, SVD algorithm source code, etc.
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Size: 9216 |
Author: 胡治权 |
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Description:
谐波恢复的ARMA建模算法(基于SVD-TLS)（张贤达《现代信号处理》）。当谐波信号为复谐波的时，该算法仍然适用。但该程序中没有给出具体的实现。-Harmonic Retrieval of ARMA modeling algorithm (based on the SVD-TLS) (Xian Tatsu Modern Signal Processing ). When the harmonic signal for the resumption of harmonics, the algorithm still applies. However, the procedure did not give a concrete realization.
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Size: 1024 |
Author: |
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Description: svd分析的例子，程序，生成数据，预处理，分析-SVD analysis of the examples, procedures, generating data, pretreatment, analysis
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Size: 1024 |
Author: 来海锋 |
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Description: 利用奇异值分解-总体最小二乘法估计ARMA模型的AR参数,并利用参数进行谐波恢复仿真程序-The use of singular value decomposition- total least squares estimation of AR parameters of ARMA model and using the parameters of harmonic retrieval simulation program
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Size: 1024 |
Author: 史龙 |
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Description: 用于谐波恢复的ESPRIT方法的SVD-TLS的程序实现，并进行了信号的谐波的恢复仿真实验-For the ESPRIT harmonic retrieval method of SVD-TLS program and conducted the restoration of harmonic signals in simulation
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Size: 1024 |
Author: 史龙 |
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Description: 使用自编函数基于奇异值分解总体最小二乘法（svd-tls）实现AR模型谱估计
-The use of self-functions in general based on singular value decomposition least square method (svd-tls) to achieve AR model spectrum estimation
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Size: 1024 |
Author: 王冰 |
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Description: 基于最小二乘法和奇异值-总体最小二乘法(SVD-TLS)的
ARMA模型谐波频率估计
-Based on the least square method and singular value- the overall least squares (SVD-TLS) of the ARMA model of harmonic frequency estimation
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Size: 1024 |
Author: wangcheng |
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Description: 基于svd算法的matlab源码，压缩.bmp格式的位图为例-Based on the SVD algorithm matlab source, compressed. Bmp format Bitmap example
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Size: 3072 |
Author: xuyan |
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Description: 基于svd-tls功率谱分析的方法 ，是现代谱估计的一种常用方法-svd-tls-based power spectral analysis method is a kind of modern spectral estimation methods commonly used
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Size: 2048 |
Author: 王宪涛 |
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Description: 功率谱估计中SVD-TLS算法的三种实现版本-Power spectrum estimation of the three kinds of SVD-TLS algorithm implementation version of the
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Size: 3072 |
Author: 平凡 |
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Description: 基于SVD_TSL算法的ARMA模型的参数估计，欢迎下载-SVD_TSL algorithm based on parameter estimation of ARMA models, please download
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Size: 2048 |
Author: francis |
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Description: SVD-TLS和LS方法估计AR模型功率谱,假定仿真的观测数据由 产生，其中w(n)是一高斯白噪声，其均值为0，方差为1，并取n=1,…..,128，这里分别用LS方法和SVD-TLS方法估计观测数据的AR模型参数。-SVD-TLS and the LS method to estimate AR model for power spectrum, assuming that the simulation produced by the observed data, where w (n) is a Gaussian white noise with mean 0 and variance 1, and take n = 1, ... .. , 128, LS methods were used here and SVD-TLS method to estimate the AR model parameters observed data.
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Size: 1024 |
Author: 云卷云舒 |
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Description: 根据张贤达版《现代信号处理》的SVD-TLS算法，基于奇异值分解的总体最小二乘法, SVD-TLS是一个在现代谱估计中一个基础的算法(SVD-TLS, Spectral estimation)
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Size: 1024 |
Author: LMQiao |
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