Estimating Signals with Finite Rate of Innovation from Noisy Samples: A Stochastic Algorithm

As an example of the recently-introduced concept of rate of innovation, signals that are linear combinations of a finite number of Diracs per unit time can be acquired by linear filtering followed by uniform sampling. However, in reality, samples are rarely noiseless. In this paper, we introduce a novel stochastic algorithm to reconstruct a signal with finite rate of innovation from its noisy samples. Even though variants of this problem has been approached previously, satisfactory solutions are only available for certain classes of sampling kernels, for example kernels which satisfy the Strang-Fix condition. In this paper, we consider the infinite-support Gaussian kernel, which does not satisfy the Strang-Fix condition. Other classes of kernels can be employed. Our algorithm is based on Gibbs sampling, a Markov chain Monte Carlo (MCMC) method. Extensive numerical simulations demonstrate the accuracy and robustness of our algorithm.Comment: Submitted to IEEE Transactions on Signal Processin

Fireball/Blastwave Model and Soft Gamma-ray Repeaters

Soft gamma-ray repeaters are at determined distances and their positions are known accurately. If observed, afterglows from their soft gamma-ray bursts will provide important clues to the study of the so called "classical gamma-ray bursts". On applying the popular fireball/blastwave model of classical gamma-ray bursts to soft gamma-ray repeaters, it is found that their X-ray and optical afterglows are detectable. Monitoring of the three repeaters is solicited.Comment: Already published in 1998 in "Chinese Physics Letters", replaced with the published version. See astro-ph/0502452 for a more detailed versio

Factors contributing to IT industry success in developing countries: the case of Thailand

A stream of research exists that explores a country's information technology (IT) industry success. The theoretical model used in these studies is primarily focused on small developed countries. We contend that the factors that contribute to IT industry success in developing countries are likely to differ somewhat from those that play a role in small developed countries. Research to date on IT industry success has neglected developing countries. This study therefore presents an alternative IT industry success model for developing countries. It adapts Ein-dor, Myers, and Raman's (1997) model in developing such a conceptual model. The adapted framework is then applied in a study of IT industry in a developing country - Thailand. We found IT-related foreign direct investment to be vital to IT industry success in Thailand. Unlike findings from earlier studies on small developed countries, geographical location and to a lesser extent government investment promotion policies are also important to IT industry success in a developing country. These findings support the view that there are differences in the factors that affect IT industry success in developed and developing countries. Implications for research and practice are discussed. © 2005 Wiley Periodicals, Inc

"Almost stable" matchings in the Roommates problem

An instance of the classical Stable Roommates problem (SR) need not admit a stable matching. This motivates the problem of finding a matching that is “as stable as possible”, i.e. admits the fewest number of blocking pairs. In this paper we prove that, given an SR instance with n agents, in which all preference lists are complete, the problem of finding a matching with the fewest number of blocking pairs is NP-hard and not approximable within n^{\frac{1}{2}-\varepsilon}, for any \varepsilon>0, unless P=NP. If the preference lists contain ties, we improve this result to n^{1-\varepsilon}. Also, we show that, given an integer K and an SR instance I in which all preference lists are complete, the problem of deciding whether I admits a matching with exactly K blocking pairs is NP-complete. By contrast, if K is constant, we give a polynomial-time algorithm that finds a matching with at most (or exactly) K blocking pairs, or reports that no such matching exists. Finally, we give upper and lower bounds for the minimum number of blocking pairs over all matchings in terms of some properties of a stable partition, given an SR instance I

Gas Kinematics and Excitation in the Filamentary IRDC G035.39-00.33

Some theories of dense molecular cloud formation involve dynamical environments driven by converging atomic flows or collisions between preexisting molecular clouds. The determination of the dynamics and physical conditions of the gas in clouds at the early stages of their evolution is essential to establish the dynamical imprints of such collisions, and to infer the processes involved in their formation. We present multi-transition 13CO and C18O maps toward the IRDC G035.39-00.33, believed to be at the earliest stages of evolution. The 13CO and C18O gas is distributed in three filaments (Filaments 1, 2 and 3), where the most massive cores are preferentially found at the intersecting regions between them. The filaments have a similar kinematic structure with smooth velocity gradients of ~0.4-0.8 km s-1 pc-1. Several scenarios are proposed to explain these gradients, including cloud rotation, gas accretion along the filaments, global gravitational collapse, and unresolved sub-filament structures. These results are complemented by HCO+, HNC, H13CO+ and HN13C single-pointing data to search for gas infall signatures. The 13CO and C18O gas motions are supersonic across G035.39-00.33, with the emission showing broader linewidths toward the edges of the IRDC. This could be due to energy dissipation at the densest regions in the cloud. The average H2 densities are ~5000-7000 cm-3, with Filaments 2 and 3 being denser and more massive than Filament 1. The C18O data unveils three regions with high CO depletion factors (f_D~5-12), similar to those found in massive starless cores.Comment: 20 pages, 14 figures, 6 tables, accepted for publication in MNRA

A Probabilistic Method For Foreground And Shadow Segmentation

10.1111/1539-6924.00371IEEE International Conference on Image Processing3937-94085QT