A projected gradient dynamical system modelling the dynamics of bargaining

We propose a projected gradient dynamical system as a model for a bargaining scheme for an asset for which the two interested agents have personal valuations that do not initially coincide. The personal valuations are formed using subjective beliefs concerning the future states of the world, and the reservation prices are calculated using expected utility theory. The agents are not rigid concerning their subjective probabilities and are willing to update them under the pressure to reach finally an agreement concerning the asset. The proposed projected dynamical system, on the space of probability measures, provides a model for the evolution of the agents, beliefs during the bargaining period and is constructed so that an agreement is reached under the minimum possible deviation of both agents from their initial beliefs. The convergence results are shown using techniques from convex dynamics and Lyapunov function theory.     

A note on the dependence on parameters for a nonlinear system via monotonicity theory

Using monotonicity theory, we investigate the continuous dependence on parameters for the discrete BVPs, which can be written in a form of a nonlinear system.     

Asymptotic periodicity of nonlinear discrete Volterra equations and applications

Sufficient conditions for the asymptotic periodicity of solutions of nonlinear discrete Volterra equations of Hammerstein type are obtained. Such results are applied to analyze the property of a class of numerical methods to preserve the asymptotic periodicity of the analytical solution of Volterra integral equations.     

A note on the well-posed anisotropic discrete BVPs

Using the direct method of the calculus of variations, we investigate the existence, uniqueness and continuous dependence on parameters for solutions of second-order discrete anisotropic equations with Dirichlet boundary conditions.     

Spectral properties of singular discrete linear Hamiltonian systems

This paper is concerned with spectral properties of singular discrete linear Hamiltonian systems. It is shown that properties of the essential spectrum of each self-adjoint subspace extension (SSE) of the corresponding minimal subspace are independent of the values of the coefficients of the system on any finite subinterval. The analyticity of the Weyl function is studied by employing the Schwarz reflection principle for the system in the limit point case. Based on the above work, several sufficient conditions are obtained for each SSE to have no essential spectrum points in an interval of the real line in the strong limit point case, and then a sufficient condition for the essential spectrum to be bounded from below (above) and a sufficient condition for the pure discrete spectrum are presented, respectively. As a direct consequence, the related spectral properties of singular higher order symmetric vector difference expressions are given.     

The generalized Krawtchouk polynomials and the fifth Painlevé equation

We study the recurrence coefficients of the orthogonal polynomials with respect to a semi-classical extension of the Krawtchouk weight. We derive a coupled discrete system for these coefficients and show that they satisfy the fifth Painlevé equation when viewed as functions of one of the parameters in the weight.     

Multiple solutions for partial discrete Dirichlet problems depending on a real parameter

In this paper we establish the existence of multiple solutions for a partial discrete Dirichlet problem depending on a real parameter. More precisely, under appropriate assumptions on the nonlinearities, we determine exact collections of parameters such that the treated problems admit at least three solutions.     

Iterative learning control for linear discrete delay systems via discrete matrix delayed exponential function approach

ABSTRACT

This paper proposes iterative learning control (ILC) for linear discrete delay systems with randomly varying trial lengths without knowing prior information on the probability distribution of random iteration length. Based on matrix delayed exponential function approach, an explicit solution to the linear discrete delay controlled systems is used to generate a sequence of outputs that approximate the desired reference by adopting two ILC update laws in the presence of randomly iteration-varying lengths. A new and direct mathematical technique is explored to deal with ILC for linear discrete delay systems. Two illustrative examples are provided to verify the theoretical results.