Galerkin Projection Methods for Solving Multiple Linear Systems

In this paper, we consider using conjugate gradient (CG) methods for solving multiple linear systems A(i) x(i) = b(i) , for 1 ≤ i ≤ s, where the coefficient matrices A(i) and the right-hand sides b( i) are different in general. In particular, we focus on the seed projection method which generates a Krylov subspace from a set of direction vectors obtained by solving one of the systems, called the seed system, by the CG method and then projects the residuals of other systems onto the generated Krylov subspace to get the approximate solutions. The whole process is repeated until all the systems are solved. Most papers in the literature [T. F. Chan and W. L. Wan, SIAM J. Sci. Comput., 18 (1997), pp. 1698­1721; B. Parlett Linear Algebra Appl., 29 (1980), pp. 323­346; Y. Saad, Math. Comp., 48 (1987), pp. 651­662; V. Simoncini and E. Gallopoulos, SIAM J. Sci. Comput., 16 (1995), pp. 917­933; C. Smith, A. Peterson, and R. Mittra, IEEE Trans. Antennas and Propagation, 37 (1989), pp. 1490­1493] considered only the case where the coefficient matrices A( i) are the same but the right-hand sides are different. We extend and analyze the method to solve multiple linear systems with varying coefficient matrices and right-hand sides. A theoretical error bound is given for the approximation obtained from a projection process onto a Krylov subspace generated from solving a previous linear system. Finally, numerical results for multiple linear systems arising from image restorations and recursive least squares computations are reported to illustrate the effectiveness of the method.published_or_final_versio

Wavelet analysis of head-related transfer functions

The directional-dependent information in the head-related transfer function (HRTF) is important for the study of human sound localization system and the synthesis of virtual auditory signals. Its time-domain and frequency-domain characteristics have been widely studied by researchers. The purpose of this paper is to explore the ability of discrete wavelet transform to describe the time-scale characteristics of HRTFs. Both the time-domain characteristics and energy distribution of different frequency subbands were studied. Discrete wavelet analysis is found to be a new direction-dependence information showing the relation of the characteristics of the HRTFs to sound source directions.published_or_final_versio

A rule-based acceleration control scheme for an induction motor

Author name used in this publication: Y. K. WongAuthor name used in this publication: S. L. Ho2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Speed estimation of an induction motor drive using an optimized extended Kalman filter

Author name used in this publication: K. L. ShiAuthor name used in this publication: Y. K. WongAuthor name used in this publication: S. L. Ho2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A simulation study on sensorless control of permanent magnet synchronous motor drives

Author name used in this publication: Tze-Fun ChanRefereed conference paper2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

From small to big molecules: how do we prevent and delay the progression of age-related neurodegeneration?

Age-related neurodegeneration in the brain and retina is complicated. It comprises a series of events encompassing different modes of degeneration in neurons, as well as inflammation mediated by glial cells. Systemic inflammation and risk factors can contribute to disease progression. Age-related conditions such as Alzheimer's disease (AD), Parkinson's disease (PD) and Age-related Macular Degeneration (AMD) affect patients for 5 to 20 years and are highly associated with risk factors such as hyperhomocysteinaemia, hypercholesterolaemia, hypertension, and symptoms of mood disorder. The long duration of the degeneration and the wide array of systemic factors provide the opportunity for nutraceutical intervention to prevent or delay disease progression. Small molecules such as phenolic compounds are candidates for neuroprotection because they have anti-oxidant activities and can modulate intracellular signaling pathways. Bigger entities such as oligosaccharides and polysaccharides have often been neglected because of their complex structure. However, certain big molecules can provide neuroprotective effects. They may also have a wide spectrum of action against risk factors. In this review we use an integrative approach to the potential uses of nutraceutical products to prevent age-related neurodegeneration. These include direct effects of phenolic compounds and polysaccharides on neurons to antagonize various neurodegenerative mechanisms in AD, PD and AMD, and indirect effects of these compounds on peripheral disease-related risk factors.postprin

Direct self control of induction motor based on neural network

Author name used in this publication: Y. K. WongAuthor name used in this publication: S. L. Ho2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A comparative study of Kalman filtering for sensorless control of a permanent-magnet synchronous motor drive

Author name used in this publication: Borsje, P.Author name used in this publication: Wong, Y. K.Author name used in this publication: Ho, S. L.Refereed conference paper2004-2005 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Randomized trial of use of incentive to increase the response rate to a mailed survey

Author name used in this publication: Tong M. F. ChanAuthor name used in this publication: Sonny H. M. TseAuthor name used in this publication: Mary C. DayAuthor name used in this publication: Edmond T. F. TongAuthor name used in this publication: Lorna K. P. Suen2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Decreasing time consumption of microscopy image segmentation through parallel processing on the GPU

The computational performance of graphical processing units (GPUs) has improved significantly. Achieving speedup factors of more than 50x compared to single-threaded CPU execution are not uncommon due to parallel processing. This makes their use for high throughput microscopy image analysis very appealing. Unfortunately, GPU programming is not straightforward and requires a lot of programming skills and effort. Additionally, the attainable speedup factor is hard to predict, since it depends on the type of algorithm, input data and the way in which the algorithm is implemented. In this paper, we identify the characteristic algorithm and data-dependent properties that significantly relate to the achievable GPU speedup. We find that the overall GPU speedup depends on three major factors: (1) the coarse-grained parallelism of the algorithm, (2) the size of the data and (3) the computation/memory transfer ratio. This is illustrated on two types of well-known segmentation methods that are extensively used in microscopy image analysis: SLIC superpixels and high-level geometric active contours. In particular, we find that our used geometric active contour segmentation algorithm is very suitable for parallel processing, resulting in acceleration factors of 50x for 0.1 megapixel images and 100x for 10 megapixel images