An SQP algorithm is presented for solving constrained nonlinear programming problems. The algorithm uses three stepsize strategies in order to achieve global and superlinear convergence. Switching rules are implemented that combine the merits and avoid the drawbacks of the three stepsize strategies. A penalty parameter is determined using an adaptive strategy that aims to achieve sufficient dec...

When the stepsize in Runge-Kutta codes is restricted by stability, an uneven pattern of stepsizes with many step rejections is frequently observed. A modiied strategy is proposed to smooth out this type of behaviour. Several new estimates for the dominant eigenvalue of the Jacobian are derived. It is shown that such estimates can be used, in a strictly controlled way, to improve the stepsize st...

In this paper, we extend the improved pointwise iteration-complexity result of a dynamic regularized alternating direction method of multipliers (ADMM) for a new stepsize domain. In this complexity analysis, the stepsize parameter can even be chosen in the interval (0, 2) instead of interval (0, (1 + √ 5)/2). As usual, our analysis is established by interpreting this ADMM variant as an instance...

We propose two low complexity adaptive step-size mechanisms based on the normalised orthogonal gradient algorithm for frequency-domain equalisation in orthogonal frequency division multiplexing (OFDM) systems. These algorithms are derived from employing a mixed-subcarrier exponentially weighted least squares criterion. Two low complexity adaptive stepsize approaches are investigated by exploiti...

It has recently been observed that with appropriate stepsize normalization, the convergence speed of the constant modulus (CM) algorithm can be dramatically improved. In this correspondence, it is shown that if a different normalization strategy is used, one that takes into account the finite alphabet structure of the signals, a standard normalized version of the decision directed equalizer (DD...

This paper presents an error test function usable for the local error contro l and the automatic stepsize selection in the numerical integration of general index-1 and index-2 differentialalgebraic equations (DAEs). This test function makes a compromise between a good approximation of the error arising per step by the discretization (local error) and the order and smoothness assumptions made by...

Markov Random Fields (MRF) minimization is a well-known problem in computer vision. We consider the augmented dual of the MRF minimization problem and develop a Mirror Descent algorithm based on weighted Entropy and Euclidean Projection. The augmented dual problem consists of maximizing a non-differentiable objective function subject to simplex and linear constraints. We analyze the convergence...

Abstract. A strategy for controlling the stepsize in the numerical integration of stochastic differential equations (SDEs) is presented. It is based on estimating the p-th mean of local errors. The strategy leads to stepsize sequences that are identical for all computed paths. For the family of Euler schemes for SDEs with small noise we derive computable estimates for the dominating term of the...

In wireless communications, multi-channel transmission is utilized to obtain high capacity and better throughput efficiency. Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) is considered as spectrally efficient system to achieve high throughput communications. This paper investigates the performance enhancement of MIMO-OFDM system using NLMS, variable ste...

Computations with two flavours of dynamical staggered quarks are quite popular at present. There are a number of possible problems with such calculations such as flavour symmetry breaking and non-locality of the square-root of the fourflavour action. In this investigation we shall ignore these and consider only the possible errors introduced through algorithmic approximations. We propose the us...