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A novel localization algorithm, which considers nonline-of-sight (NLOS) propagation, is proposed in this paper. By introducing a transfer function that relates the field at a given receiver to the source as a function of frequency and position, the NLOS effect can be mitigated and the propagation channel can be calibrated back to free space. The simulation results demonstrate that the proposed algorithm performs much better than that using the usual line-of-sight time difference of arrival (TDOA) localization, and the accuracy is only limited by the sampling frequency. The measurements verify the improvement in using the improved TDOA method versus the usual TDOA method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new iterative scheme with the help of the gradientprojection algorithm (GPA) for finding a common solution of an equilibrium problem, a constrained convex minimization problem, and a fixed point problem. Then, we prove some strong convergence theorems which improve and extend some recent results. Moreover, we give a numerical result to show the validity of our main theorem. [ABSTRACT FROM AUTHOR]

For finding a common solution of generalized equilibrium problem, fixed point problem and the zero points of the sum of two operators, a regularization algorithm is established in the framework of real Hilbert spaces. And the strong convergence theorem is obtained under certain assumptions. The main results presented in this paper are useful in nonlinear analysis and optimization. Moreover, the results and corollaries extend the corresponding conclusions proposed by many authors. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a new mapping for a finite family of accretive operators and introduce an iterative algorithm for finding a common zero of a finite family of accretive operators in a real reflexive strictly convex Banach space which has a uniformly Gâteaux differentiable norm and admits the duality mapping jφ, where φ is a gauge function invariant on [0, ∞). Furthermore, we prove the strong convergence under some certain conditions. The results obtained in this paper improve and extend the corresponding ones announced by many others. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a split hierarchical monotone variational inclusion problem (SHMVIP) which includes split variational inequality problems, split monotone variational inclusion problems, split hierarchical variational inequality problems, etc., as special cases. An iterative algorithm is proposed to compute the approximate solutions of an SHMVIP. The weak convergence of the sequence generated by the proposed algorithm is studied. We present an example to illustrate our algorithm and convergence result. [ABSTRACT FROM AUTHOR]

Solving equations of the form H ( x ) = 0 is usually done by applying iterative methods. The main interest of this paper is to improve the domain of starting points for Steffensen’s method. In general, the accessibility of iterative methods that use divided differences in their algorithms is reduced, since there are difficulties in the choice of starting points to guarantee the convergence of the methods. In particular, by using a decomposition of the operator H and applying a special type of iterative methods, which combine two iterative schemes in the algorithms, we can improve the accessibility of Steffensen’s method. Moreover, we analyze the local convergence of the new iterative method proposed in two cases: when H is differentiable and H is non-differentiable. The dynamical properties show that the method also improves the region of accessibility of Steffensen’s method for non-differentiable operators. So, we present an alternative for the non-applicability of Newton’s method to non-differentiable operators that improves the accessibility of Steffensen’s method. The theoretical results are illustrated with numerical experiments. [ABSTRACT FROM AUTHOR]

This paper presents an iterative algorithm for G 2 multiwise merging of Bézier curves. By using the G 2 constraint, the L 2 distance is represented after simplification as a quartic polynomial in two parameters relating to the magnitudes of end tangents of the merged curve. These two parameters are restricted in a feasible region, in order for the merged curve to preserve the specified directions of end tangents. Then G 2 multiwise merging is formulated as a constrained minimization problem, and the classic projected Newton method is applied to find the minimizer. Some extensions of multiwise merging using G 3 constraints, other energy functionals and curve representations are also outlined. Several comparative examples are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers the stochastic systems described by the autoregressive output error autoregressive (AR-OEAR) models. The AR-OEAR model is a special output error model which has an extra autoregressive term of the output signal. Basing on the auxiliary model idea, the recursive method and the iterative principle, the auxiliary model based recursive and iterative least squares algorithms are proposed to estimate the parameters of the autoregressive output error autoregressive system which contains the autoregressive output error system model and the autoregressive noise model, respectively. The simulation results indicate that the proposed algorithms can work well. [ABSTRACT FROM AUTHOR]

In the present paper, we propose an iterative algorithm for solving the generalized (P, Q)-reexive solution of the quaternion matrix equation Σul=1 AlXBl + Σvs=1 CsX̃Ds = F. By this iterative algorithm, the solvability of the problem can be determined automatically. When the matrix equation is consistent over a generalized (P, Q)-reexive matrix X, a generalized (P, Q)-reexive solution can be obtained within finite iteration steps in the absence of roundoff errors, and the least Frobenius norm generalized (P, Q)-reexive solution can be obtained by choosing an appropriate initial iterative matrix. Furthermore, the optimal approximate generalized (P, Q)-reexive solution to a given matrix X0 can be derived by finding the least Frobenius norm generalized (P, Q)-reexive solution of a new corresponding quaternion matrix equation. Finally, two numerical examples are given to illustrate the efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the problem of solving the general coupled matrix equations (including several linear matrix equations as special cases) which plays important roles in system and control theory. Based on the conjugate gradients squared (CGS) method, a simple and efficient matrix algorithm is derived to solve the general coupled matrix equations. The derived iterative algorithm is illustrated by two numerical examples and is compared with other popular iterative solvers in use today. [Copyright &y& Elsevier]

Power method is frequently used for finding largest Eigen-pair. On the other hand, Inverse Power method is utilized to find smallest Eigen-pair. Using shifting property, Power method and/or Inverse Power method can be used to find out other desired Eigen pairs too. Several lemmas based on Power method with shifting property are presented here. Moreover, a Modified Hybrid Iterative Algorithm based upon both Power method and Inverse Power method is proposed to find both largest and smallest Eigen-pairs simultaneously with ease. Several experiments have been performed to investigate the robustness and effectiveness of the algorithm. The proposed algorithm is able to find both (largest and smallest) Eigen-pairs successfully and efficiently. Moreover, the proposed algorithm is able to find out the nature (positive and negative sign) of the Eigen values and in some cases the algorithm is also able to find out the second largest Eigen pair in consequence. [ABSTRACT FROM AUTHOR]