Problem with the distance matrix. Error termination via Lnk1e in C:\G09W\l202.exe at Wed Jan 16 20:33:11 2019. 复制代码成因:有至少两个原子间距离太近,很有可能距离是0。例如上述的报错中的一串数字写明了是:6号原子和1号原子之间太近,7号和2号太近,8号和3号太近,etc ...
我在用oniom优化一个分子筛晶体结构的时候，计算终止并提示Problem with the distance matrix. 有一部分...
Harris functional with IExCor= 402 and IRadAn= 5 diagonalized for initial guess.HarFok: I...
Form the distance matrix for use in a Gaussian ProcessAlex Lenkoski
7. Problem with the distance matrix.(距离矩阵) Error termination via Lnk1e in /pkg/gaussian/g03/l202.exe Solution: Try to restart optimization from a different input geometry.(重新不同几何异构体的输入优化) New curvilinear step not converged(新曲线步骤不收敛). Error imposing constraints ...
In this paper, we consider the convergence of Gaussian BP, focusing in particular on the convergence of the information matrix. We show analytically that the exchanged message information matrix converges for arbitrary positive semidefinite initial value, and its distance to the unique positive definite...
For the system in Eq. (2.28), the Gaussian white noise {w} on states and Gaussian white noise {v} on output has the following statistical expectations with respect to their mean and autocorrelations. The mean vector and autocorrelation matrix of w and v are: (2.29)μw=Ew=0,Rww=EwwT=...
, and the problem (I assume) is that this is a transposed square root. Using a symmetric squre root, meaning a matrix square rootSsuch that might just solve your problem. I use the below code with no problems. function[dist] = GW_dist(mu_1, cov_1, mu_2, cov_2) ...
where Od×d denotes the d×d zero matrix. For deriving the maximum likelihood solutions, formulas for vector and matrix derivatives shown in Fig. 12.3 are useful. Indeed, the partial derivatives of the log-likelihood with respect to vector μ and matrix Σ are given by Sign in to download...
For example, when applied to the problem of compression, the entropy of the distributions described above is significantly less than that of a Gaussian with the same variance, and this leads directly to gains in coding efficiency. In denoising, the use of this model as a prior density for ...