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Wavelet Analysis of Space Solar Telescope Images 总被引:1,自引:0,他引:1
Xi-An Zhu Sheng-Zhen Jin Jing-Yu Wang Shu-Nian NingNational Astronomical Observatories Chinese Academy of Science Beijing Department of Mechanical Electric Engineering China College of Mining Technology Beijing 《中国天文和天体物理学报》2003,3(6):587-596
The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job. 相似文献
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WANGXie-kang HUANGEr CUIPeng 《中国地理科学(英文版)》2003,13(3):262-266
Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed. 相似文献
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The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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形变大地测量学的进展、问题与地震预报 总被引:12,自引:7,他引:5
简要概括了形变大地测量学的革命性进展,研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”,但也存在不少急待解决的问题。着重研讨了在21世纪前10年,形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术,开展创新性研究和试验以推进地震预报。为此,对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。 相似文献
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I.A. Bond F. Abe R.J. Dodd J.B. Hearnshaw M. Honda J. Jugaku P.M. Kilmartin A. Marles K. Masuda Y. Matsubara Y. Muraki T. Nakamura G. Nankivell S. Noda C. Noguchi K. Ohnishi N.J. Rattenbury M. Reid To. Saito H. Sato M. Sekiguchi J. Skuljan D.J. Sullivan T. Sumi M. Takeuti Y. Watase S. Wilkinson R. Yamada T. Yanagisawa P.C.M. Yock 《Monthly notices of the Royal Astronomical Society》2001,327(3):868-880
We describe observations carried out by the MOA group of the Galactic bulge during 2000 that were designed to detect efficiently gravitational microlensing of faint stars in which the magnification is high and/or of short duration. These events are particularly useful for studies of extrasolar planets and faint stars. Approximately 17 deg2 were monitored at a sampling rate of up to six times per night. The images were analysed in real time using a difference imaging technique. 20 microlensing candidates were detected, of which eight were alerted to the microlensing community whilst in progress. Approximately half of the candidates had high magnifications (≳10), at least one had very high magnification (≳50), and one exhibited a clear parallax effect. The details of these events are reported here, together with details of the on-line difference imaging technique. Some nova-like events were also observed and these are described, together with one asteroid. 相似文献
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We have analysed short-exposure high-resolution images obtained on the William Herschel Telescope (WHT), Big Telescope Azimuthal (BTA) and CanadaFranceHawaii Telescope (CFHT) in order to investigate mechanical vibrations that are capable of reducing the high angular resolution allowed by speckle-interferometric methods. After filtering the photon noise we have computed power spectra of the image centres of gravity. In these spectra we have found vibration features that differ from one telescope to another and that vary in particular with the zenith angle. In the case of the WHT we discuss these results in terms of possible causes and in terms of degradation of the transfer function. We present some means to improve the data. 相似文献