This article deals with the convergence of quantum-inspired evolutionary algorithms with one quantum individual and multiple observations. Applying the theory and analytical techniques in non-homogeneous Markov chain, we obtain the conclusion that quantuminspired evolutionary algorithms could converge in probability under some mild conditions imposed on the probability amplitude of the Q-bit in...

Low codimensional bifurcations of control systems have been classified using the theory of normal forms. However, the normal form theory was developed as local results. To understand the behavior of control systems outside a local area of a bifurcation point, it is necessary to study the convergence of the normal forms if the vector fields are analytic. The convergence is a long time open probl...

In this paper we investigate the stability and convergence rates of the widely used output least-squares method with Tikhonov regularization for the identification of the conductivity distribution in a heat conduction system. Due to the rather restrictive source conditions and regularity assumptions on the nonlinear parameter-to-solution operator concerned, the existing Tikhonov regularization ...

In order to achieve the best filtering performance and make the filter automatically adjust its coefficients with the changing of its working environment, we need to use adaptive filter technique. To overcome the contradiction of traditional LMS algorithm between convergence speed, convergence accuracy and the selection of step-size, a novel variable step-size & variable parameters adaptive fil...

We analyze the use of edge finite element methods to approximate Maxwell’s equations in a bounded cavity. Using the theory of collectively compact operators, we prove h-convergence for the source and eigenvalue problems. This is the first proof of convergence of the eigenvalue problem for general edge elements, and it extends and unifies the theory for both problems. The convergence results are...

The concave-convex procedure (CCCP) is an iterative algorithm that solves d.c. (difference of convex functions) programs as a sequence of convex programs. In machine learning, CCCP is extensively used in many learning algorithms, including sparse support vector machines (SVMs), transductive SVMs, and sparse principal component analysis. Though CCCP is widely used in many applications, its conve...

This paper develops a computational model for nonlinear bending analysis of functionally graded (FG) plates using a four-node quadrilateral element SQ4T within the context of the first order shear deformation theory (FSDT). In particular, the construction of the nonlinear geometric equations are based on Total Lagrangian approach in which the motion at the present state compared with the initia...

We present and analyze a class of evolutionary algorithms for unconstrained and bound constrained optimization on R(n): evolutionary pattern search algorithms (EPSAs). EPSAs adaptively modify the step size of the mutation operator in response to the success of previous optimization steps. The design of EPSAs is inspired by recent analyses of pattern search methods. We show that EPSAs can be cas...

The notion of convergence has gained a lot of interest in the past few years in both theory and practice. On one hand, observers see convergence as a meaningless technology fad. Other observers, on the other hand consider convergence to be an important factor for the design of new mobile information infrastructures and services. This paper investigates these contradictory discourses by applying...

We analyze the use of edge finite element methods to approximate Maxwell’s equations in a bounded cavity. Using the theory of collectively compact operators, we prove h-convergence for the source and eigenvalue problems. This is the first proof of convergence of the eigenvalue problem for general edge elements, and it extends and unifies the theory for both problems. The convergence results are...