1) Approximate Cholesky Factorization
近似Cholesky分解
2) Cholesky decomposition
Cholesky分解
1.
An improved Cholesky decomposition method based on DSP implement in joint Detection;
一种基于DSP实现的改进Cholesky分解方法
2.
FPGA implementation of configurable matrix inversion based on Cholesky decomposition
基于Cholesky分解的可配置矩阵求逆FPGA实现
3.
Performance evaluation of Cholesky decomposition parallel algorithm
Cholesky分解并行算法的性能评测
3) Cholesky factorization
Cholesky分解
1.
Rice condition numbers of QR and Cholesky factorizations;
QR分解和Cholesky分解的Rice条件数(英文)
2.
The fast hyperbolic transformation in hyperbolic Cholesky factorization;
双曲Cholesky分解中的快速双曲旋转变换
3.
By using the Cholesky factorization and inverse method for unit lower triangular matrix, the multi-sensor measurement model with correlated measurement noises is transformed to an equivalent pseudo one with uncorrelated measurement noises; then based on the Markov estimation, a new multi-sensor data fusion method with correlated measurement noises is proposed.
对于测量噪声相关的多传感器测量模型,利用Cholesky分解和单位下三角阵的求逆方法,将其转化为测量噪声互不相关的等价的多传感器伪测量模型,然后基于Markov估计,提出了一种测量噪声相关情况下多传感器数据融合的新方法。
4) Cholesky factorization
Cholesky分解法
1.
A graph model for Cholesky factorization dealing with symmetric positive coefficient matrix is proposed.
通过对Cholesky分解法求解线性方程组的分析 ,建立Cholesky分解法三角化对称正定阵的图模型 ,并基于该模型及Mesh结构P/G网络的自身特点 ,提出一个P/G网快速分析算法 实验证明 ,该算法能大大降低Mesh结构P/G网络的分析运算时间和内存占
2.
Cholesky factorization technique is used to shorten the run-time of sub-network computation.
其中,对于子网运算,通过对Cholesky分解法三角化对称正定阵的图模型分析,并基于Mesh结构网络的自身特点,提出了一个基于图顶点排序的加速子网分析运算策略;并用基于MPI的并行结构实现了P/G布线网络分析的并行运算。
3.
To shorten the run-time of computing sub-net using Cholesky factorization technique, a graph model for Cholesky factors dealing with symmetric positive coefficient matrix is discussed and a novel technique based on vertex sorting and removing is presented.
其中,对于子网运算,通过对Cholesky分解法三角化对称正定阵的图模型分析,提出了基于图顶点消去排序的加速子网分析运算策略,并用基于MPI的并行结构实现了P/G网分析的并行运算。
5) Cholesky-like factorization
Cholesky-like分解
1.
Every real skew-symmetric matrix B admits Cholesky-like factorizations B=R~T J R,where J=(0 (-I) I 0),R is a permuted triangular matrix.
设实反对称矩阵B的Cholesky-like分解为B=R~TJR,其中J=(0 (-I) I 0),R是上三角矩阵的重排。
6) Cholesky factorization
Cholesky因式分解
补充资料：近似
相近或相像但不相同：这两个地区的方音有些～。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条