task graph scheduling is a multi-objective optimization and np-hard problem. in this paper a new algorithm on homogeneous multiprocessors systems is proposed. basically, scheduling algorithms are targeted to balance the two parameters of time and energy consumption. these two parameters are up to a certain limit in contrast with each other and improvement of one causes reduction in the other on...

The run time of many scientific computation applications for numerical methods is heavily dependent on just a few multi-dimensional loop nests. Since these applications are often limited by memory bandwidth rather than computational resources they can benefit greatly from any optimizations which decrease the run time of their loops by improving data reuse and thus reducing the total memory traf...

This paper presents an approach to compute the neighboring extremal solution for an optimal switched impulsive control problem with a pre-specified sequence of modes and a large perturbation in the initial state. The decision variables – the subsystem switching times and the control parameters – are subject to inequality constraints. Since the active status of these inequality constraints may c...

We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually contain non-Gaussian noise and outliers, which makes non-robust estimation methods ineffective. In this paper, we propose an overview of a Lagrangian formulation of the Half-Quadratic approach by, first, revisiting the der...

We present a novel plane tracking algorithm based on the direct update of surface parameters from two stereo images. The plane tracking algorithm is posed as an optimization problem, and maintains an iteratively re-weighted least squares approximation of the plane’s orientation using direct pixel-measurements. To facilitate autonomous operation, we include an algorithm for robust detection of s...