Discovery of Spatial Periodicities in a Coronal Loop Using Automated Edge-Tracking Algorithms

A new method for automated coronal loop tracking, in both spatial and temporal domains, is presented. Applying this technique to TRACE data, obtained using the 171 angstrom filter on 1998 July 14, we detect a coronal loop undergoing a 270 s kink-mode oscillation, as previously found by Aschwanden et al. However, we also detect flare-induced, and previously unnoticed, spatial periodicities on a scale of 3500 km, which occur along the coronal loop edge. Furthermore, we establish a reduction in oscillatory power for these spatial periodicities of 45% over a 222 s interval. We relate the reduction in detected oscillatory power to the physical damping of these loop-top oscillations.

Custom coprocessor based matrix algorithms for image and signal processing

Matrix algorithms are important in many types of applications including image and signal processing. A close examination of the algorithms used in these, and related, applications reveals that many of the fundamental actions involve matrix algorithms such as matrix multiplication. This paper presents an investigation into the design and implementation of different matrix algorithms such as matrix operations, matrix transforms and matrix decompositions using a novel custom coprocessor system for MATrix algorithms based on Reconfigurable Computing (RCMAT). The proposed RCMAT architectures are scalable, modular and require less area and time complexity with reduced latency when compared with existing structures.

Imaging the genetics of executive function

Recent advances in neuroimaging technologies have allowed ever more detailed studies of the human brain. The combination of neuroimaging techniques with genetics may provide a more sensitive measure of the influence of genetic variants on cognitive function than behavioural measures alone. Here we present a review of functional magnetic resonance imaging (fMRI) studies of genetic links to executive functions, focusing on sustained attention, working memory and response inhibition. In addition to studies in the normal population, we also address findings from three clinical populations: schizophrenia, ADHD and autism spectrum disorders. While the findings in the populations studied do not always converge, they all point to the usefulness of neuroimaging techniques such as fMRI as potential endophenotypes for parsing the genetic aetiology of executive function. (C) 2007 Elsevier B.V. All rights reserved.

Equalisation of time variant multipath channels using amplitude banded LMS algorithms

For the purpose of equalisation of rapidly time variant multipath channels, we derive a novel adaptive algorithm, the amplitude banded LMS (ABLMS); which implements a nonlinear adaptation based on a coefficient matrix. Then we develop the: ABLMS algorithm as the adaptation procedure for a linear transversal equaliser (LTE) and a decision feedback equaliser (DFE) where a parallel adaptation scheme is deployed. Computer simulations demonstrate that with a small increase of computational complexity, the ABLMS based parallel equalisers provide a significant improvement related to the conventional LMS DFE and the LMS LTE in the case of a second order Markov communication channel model.