Dabrowski, A.: The largest transversal Lyapunov exponent and master stability function from the perturbation vector and its derivative dot product (TLEVDP). Nonlinear Dyn. 69 (3), 1225–1235 (2012) MathSciNetDabrowski, A. (2012) The largest Transversal Lyapunov Exponent and Master Stability ...
As a fast and high-quality clustering method in the data processing field, KK-means and its derivative algorithms have been commonly studied and perform well in document clustering tasks. The kernel part of KK-means algorithm focuses on the similarity measurement between the input vector and the ...
8.2: A 96.9%-Peak-Efficiency Bilaterally-Symmetrical Hybrid Buck-Boost Converter Featuring Seamless Single-Mode Operation, Always-Reduced Inductor Current, and the Use of All CMOS Switches 8.3: A Li-ion-Battery-Input 1-to-6V-Output Bootstrap-Free Hybrid Buck-or-Boost Converter Without RHP Zero ...
max_length = maxs[0] - mins[0]# Rotation matrix is the covariance matrix, but we want Z as the leading# eigenvector:rot = np.c_[-pc[2], pc[1], pc[0]]# Transform model to have zero mean, reasonable scale and rotation.self.transform(rot, np.dot(rot, -mean), float(scale) /...
el = self.element[i]# present element#Displacement formatted for an elementdisp=py.array([d[el[0]][0],d[el[0]][1],d[el[1]][0],d[el[1]][1],d[el[2]][0],d[el[2]][1]])#Element Strain vector = Product of Strain Matrix and Displacement[J,B] = self.B(el) ...
input_signal and teaching_signal must be a column vector notice that input_signal is u(n+1) and output is output(n+1) this step makes state(n) -> state(n+1) the x_history is a list of state's state_history , every item is a row vector like (100L,)""" if input_signal !=...
Input: measurement vectorb, sampling matrixA, gradient calculation matrixG; algorithm parametersρ,μ1max,μ2max; Initializationy1 = 0,y2 = 0; whilenot convergeddo 1. updategaccording to Eq. (s4); 2. updatexaccording to Eq. (s8); ...
Going into further detail, the microscopic quantum mechanical model represents the state of a QCA cell using two three-dimensional vectors: the coherence vector and the energy vector. The coherence vector λ⃗=(λx,λy,λz)λ→=λx,λy,λz...
of using a tri-axial ellipsoidal nano-antenna (NA) surrounded by a solute for enhancing light emission of near-by dye molecules, we analyze the possibility of controlling and manipulating the location of quantum dots (similar to optical tweezers) placed near NA stagnation points, by means of ...
Chapter 10 Eigenvalues and Singular Values This chapter is about eigenvalues and singular values of matrices. Computational algorithms and sensitivity to perturbations are both discussed. 10.1 Eigenvalue and Singular Value Decompositions An eigenvalue and eigenvector of a square matrix A are a scalar ...