This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computa...

‎In this paper‎, ‎we propose a feasible interior-point method for‎ ‎convex quadratic programming over symmetric cones‎. ‎The proposed algorithm relaxes the‎ ‎accuracy requirements in the solution of the Newton equation system‎, ‎by using an inexact Newton direction‎. ‎Furthermore‎, ‎we obtain an‎ ‎acceptable level of error in the inexact algorithm on convex‎ ‎quadratic symmetric cone programmin...

  We present a new full Nesterov and Todd step infeasible interior-point algorithm for semi-definite optimization. The algorithm decreases the duality gap and the feasibility residuals at the same rate. In the algorithm, we construct strictly feasible iterates for a sequence of perturbations of the given problem and its dual problem. Every main iteration of the algorithm consists of a feasibili...

We describe an iterative method that extracts the underlying soliton from a noisy pulse. The method is formulated as a functional iteration: at each step, the soliton component of the difference between the noisy pulse and the current underlying soliton is determined via soliton perturbation theory; this is then added to the soliton, and the process is repeated. We show that this iteration conv...

This paper proposes an implicit surface reconstruction algorithm based on Self-Organising Maps (SOMs). The SOM has the connectivity of a regular 3D grid, each node storing its signed distance from the surface. At each iteration of the basic algorithm, a new training set is created by sampling regularly along the normals of the input points. The main training iteration consists of a competitive ...

We present a convex nondifferentiable minimization algorithm of proximal bundle type that does not rely on measuring descent of the objective function to declare the so-called serious steps; rather, a merit function is defined which is decreased at each iteration, leading to a (potentially) continuous choice of the stepsize between zero (the null step) and one (the serious step). By avoiding th...

(b) (c) (d) (e) (f) Fig. 4. Example of the algorithm's performance. (a), (b) Phase 1, hand reorientation; (c) to (f) { hand approach and grasp execution: (c) a rst contact with the object is made, (d),(e) two intermediate positions. The nal position is shown in (f) and in Figure 5. Fig. 5. Two views of the nal position of the hand and the object shown in Figure 4(f). References 1] C. Laugier, A...

Modification of Newtons method with higher-order convergence is presented. The modification of Newtons method is based on Frontinis three-order method. The new method requires two-step per iteration. Analysis of convergence demonstrates that the order of convergence is 6. Some numerical examples illustrate that the algorithm is more efficient and performs better than classical Newtons method and ...

b c d e f Fig. 4. Example of the algorithm's performance. a, b Phase 1, hand reorientation; c to f hand approach and grasp execution: c a rst contact with the object is made, d,e two i n termediate positions. The nal position is shown in f and in Figure 5. Fig. 5. Two views of the nal position of the hand and the object shown in Figure 4f. 88 D. Reznik and V. Lumelsky. Sensor-based motion plann...

A one-step iteration with errors is considered for a family of asymptotically nonexpansive nonself mappings. Weak convergence of the purposed iteration is obtained in a Banach space.