Description: Recursive weighted partial least squares (rPLS):
an ef fi cient variable selection method using PLS-Recursive weighted partial least squares (rPLS):
an ef fi cient variable selection method using PLS Platform: |
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Author:Yongwei FU |
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Description: The Recursive least squares (RLS) is an adaptive filter which recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity. Platform: |
Size: 9216 |
Author:rajendra |
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Description: 基本最小二乘法、加权最小二乘法（包括一次完成、递推算法）、最小二乘适应算法（包括遗忘因子法、限定记忆法）以及进行偏差补偿的最小二乘法，有详细的文档说明，程序注释也很详尽-The basic method of least squares, weighted least squares method (including a complete, recursive algorithm), least squares adaptation algorithm (including forgetting factor method, limited memory method) as well as bias compensation least squares method, a detailed description of the document, the program Notes also very detailed Platform: |
Size: 136192 |
Author:liushen |
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Description: RLS 递归最小二乘滤波器算法！！！！！！！！！！！！！！！！！！！！！(Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity.) Platform: |
Size: 1024 |
Author:清微
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Description: 递归最小二乘(RLS)是一种自适应滤波算法，它可以递归地找到最小化加权线性最小二乘代价函数与输入信号相关的系数。这种方法与其他算法相比较，例如最小均方(LMS)，旨在减少均方误差。在RLS的推导中，输入信号被认为是确定性的，而对于LMS和类似的算法，它们被认为是随机的。(Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic.) Platform: |
Size: 1024 |
Author:大东东 |
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Search - weighted recursive least squares