The principal factor in the proofs of many so-called intersection results and associated best approximation theorems—such as the famed Brouwer fixed-point theorem) is Knaster-Kuratowski-Mazurkiewicz theorem (KKM), which was extended from Rl to Hausdorff vector spaces by Ky Fan. This kind of theory necessitates introducing some form of abstract convex structure on a topological space. In both pure and applied mathematics, the theory of approximation plays a central role. The connection between best approximation and fixed-point theory provides a powerful tool for analyzing the nonlinear maps, the convergence of iterative processes, and the solving of variational problems. This paper is dedicated to presenting a new extension of the well-known Prolla’s theorem in the field of invariant approximation from a normed space to a kind of metric space. First, we will introduce the basic concepts of vector metric spaces, define the best approximation, and describe its relationship to fixed points. Second, we will substantiate the best approximation theorem using the state of KKM-map (where the convex combination of any finite elements in Θ⊂Π entirely belonged to the union of their images under the KKM-map,N,N:Θ→2Π). This theoretical construction has been applied to specific cases that were previously discussed as the best approximations in earlier papers.
The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
... Show MoreThe purpose of this paper is to find the best multiplier approximation of unbounded functions in –space by using some discrete linear positive operators. Also we will estimate the degree of the best multiplier approximation in term of modulus of continuity and the averaged modulus.
The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr
This study presents the multi criteria single-machine model. The machine scheduling problem (MSP) for ntasks on a single machine involves minimizing a function of three criteria: total completion time (C_j),maximum earliest (E_max), and tardiness (〖ΣT〗_j), This is an NP-hard issue. Within this work's theoretical section, we present the mathematical formulation of The presented topic thenhighlights the usefulness of the dominance rule (DR), which may be used to develop effective solutions. Whilein the practical part, one of the important exact methods; The proposed MSP tricriteria are solved by applyingthe Branch and Bound (BAB) method, which finds a set of efficient solutions for 1//F(ΣC_j ,ΣT_j ,E_max) upto n=100 jobs. The BAB appro
... Show MoreIn this work, a weighted H lder function that approximates a Jacobi polynomial which solves the second order singular Sturm-Liouville equation is discussed. This is generally equivalent to the Jacobean translations and the moduli of smoothness. This paper aims to focus on improving methods of approximation and finding the upper and lower estimates for the degree of approximation in weighted H lder spaces by modifying the modulus of continuity and smoothness. Moreover, some properties for the moduli of smoothness with direct and inverse results are considered.