1.57]. This means that the mesh sequence is shape and contact regular and has optimal polynomial approximation properties. We denote the regularity parameter of by \rho . The faces of a mesh are collected in the set , which is decomposed into the set of interior faces or interfaces and the...
\ldots ,-N)\), we have\({\mathcal {F}}_{\lambda ({\vec {y}})}\equiv 1\). Hence the global energy function and characteristic function are both constant 1 for the step initial condition. In general since the roots of the Bethe polynomial\(q_z(w)\)depend analytically onz, ...
This system provides multiple positive effects over an individual rocket task, involving the capacity to boost and/or facilitate outreach by means of deeper starting point assessments, a high rate of failure tolerance, real-time reconfigurability, adaptability to extremely fluctuating requirements and ...
It means that the orthogonality condition for integer transforms ICT8-II (a, b, c, d, e, f, g) given by (5.58) actually corresponds to the orthogonality condition for integer transforms ICT4-IV(a, b, c, d). Thus, the integer transforms ICT2-II(g), ICT2-IV(e, f) and ICT4-...
On a More Accurate Half-Discrete Hilbert's Inequality with Non-Homogeneous Kernel By means of weight coefficient and the improved Euler-Maclaurin summation formula,a more accurate half-discrete Hilbert's inequality with the non-homogeneo... BC Yang - 《Journal of Southwest China Normal University...
(); $M = $A->rowMeans(); $M = $A->columnMeans(); // Matrix norms - return a value $‖A‖₁ = $A->oneNorm(); $‖A‖F = $A->frobeniusNorm(); // Hilbert–Schmidt norm $‖A‖∞ = $A->infinityNorm(); $max = $A->maxNorm(); // Matrix reductions $ref = $A->...
By means of discrete cyclic coordinate descent, at each step SDH solves the associated binary optimization and obtains an analytical solution, which thus makes the whole optimization very efficient. We show that direct optimization of the discrete bits with- out relaxation plays critical roles in ...
4A, B). The distribution of pixels grey-scale intensities was then divided in two groups using the k-means clustering algorithm (Supplementary Fig. 4C) to generate a binary image of black and white pixels (Supplementary Fig. 4D). Closed curves connecting white pixels adjacent to black pixels ...
Wang Q, Wang Y, Niu R, Peng L (2017) Integration of information theory, K-means cluster analysis and the logistic regression model for landslide susceptibility mapping in the Three Gorges Area. China Remote Sens 9:938 Article Google Scholar Wang H, Xiao T, Li X, Zhang L, Zhang L (20...
The goal of FDA is to find the vector w that maximises the distance between the projected means, whilst ensuring that the within-class variance remains small. Mathematically speaking, this is represented by maximising the functional $$J(\mathbf{w}) = \frac{ \left( \mathbf{w}^{T}(\hat...