The definition of the standard derivative operator is extended from integer steps to arbitrary stepsize. The classical, nonrelativistic Hamiltonian is quantized, using these new fractional operators. The resulting Schroedinger type equation generates free particle solutions, which are confined in space. The angular momentum eigenvalues are calculated algebraically. It is shown, that the charmon...

In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show t...

We consider an incremental gradient method with momentum term for minimizing the sum of continuously differentiable functions. This method uses a new adaptive stepsize rule that decreases the stepsize whenever sufficient progress is not made. We show that if the gradients of the functions are bounded and Lipschitz continuous over a certain level set, then every cluster point of the iterates gen...

In this article, we propose a method to adapt stepsize parameters used in reinforcement learning for dynamic environments. In general reinforcement learning situations, a stepsize parameter is decreased to zero during learning, because the environment is generally supposed to be noisy but stationary, such that the true expected rewards are fixed. On the other hand, we assume that in the real wo...

Approximate value iteration is used in dynamic programming when we use random observations to estimate the value of being in a state. These observations are smoothed to approximate the expected value function, leading to the problem of choosing a stepsize (the weight given to the most recent observation). A stepsize of 1/n is a common (and provably convergent) choice. However, we prove that it ...

Two-step W-methods are linearly implicit time-stepping methods using s external stages that may be processed in parallel. Methods with order s + 1 and stage order s exist. Appropriate generalizations for the concepts of A-and L-stability are derived as well as necessary conditions for A-stability and suucient conditions for stii accuracy. We construct methods of order four where no order reduct...

This paper considers the asymptotic stability analysis of both exact and numerical solutions of the following neutral delay differential equation with pantograph delay. ⎧⎨ ⎩ x′(t) +Bx(t) + Cx′(qt) +Dx(qt) = 0, t > 0, x(0) = x0, where B,C,D ∈ Cd×d, q ∈ (0, 1), and B is regular. After transforming the above equation to non-automatic neutral equation with constant delay, we determine sufficient co...

In the numerical solution of ODEs by implicit time-stepping methods, a system of (nonlinear) equations has to be solved each step. It is common practice to use xed-point iterations or, in the stii case, some modiied Newton iteration. The convergence rate of such methods depends on the stepsize. Similarly, a stepsize change may force a refactorization of the iteration matrix in the Newton solver...

The purpose of this manuscript is to derive new convergence results for several subgradient methods for minimizing nonsmooth convex functions with Hölderian growth. The growth condition is satisfied in many applications and includes functions with quadratic growth and functions with weakly sharp minima as special cases. To this end there are four main contributions. First, for a constant and su...