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Most wavelet-based denoising algorithms use the standard wavelet transform. Recently, the dual-tree complex wavelet transform (DTCWT) has been proposed as a novel analysis tool featuring near shift-invariance which is important to improve the denoising performance. In this paper, a spectra denoising algorithm based on the DTCWT is proposed. Experimental(More)
Sequence alignment reveals the relations between the characters in different sequences, and there are the reverse complement relations between the characters in DNA double strand. We introduce sequence alignment to the field of DNA computing, propose the definitions of complement alignment and reverse complement alignment, give a method of computing the(More)
The aim of astronomical spectra denoising is to reduce the noise level, while preserving astrophysical information hidden in spectra. Many astronomical spectra denoising approaches exist, in which wavelet thresholding approaches are widely adopted in many literatures. For spectra denoising using wavelet thresholding, the thresholding function greatly(More)
The current practice of recognition spectra manually is no longer applicable to a large extent. This work is particularly focused on helping astronomers finding their interesting celestial objects. In this paper an efficient hierarchical clustering data mining method based on principal component analysis (PCA) is proposed. Massive stellar spectral data are(More)
Classifying stellar spectra is an important work in astronomy. Numerous automated classification techniques have been explored for spectra data classification. But achieving high accuracy of spectral classification is still a goal of study. Random Forest is a recently available ensemble learning algorithm. Existing literatures have shown the superior(More)
—In astronomy, the Charge Coupled Device (CCD) images obtained from celestial observations are usually stored in Flexible Image Transport System (FITS) format and the sizes of such images are usually very large, 8 Megabytes or more being no unusual. Moreover, the amount of such images is very great due to continuous celestial observations. So the demand of(More)
describes in detail the method to process the characteristics of the spectral lines using the Gaussian fitting based on the least-squares method. By separately truncating the peak area data and statistically analyzing and setting fitting parameters, multiple peaks overlap interference can be better avoided, and more accurate fitting of spectral(More)