missing data imputation: a fuzzy k-means clustering algorithm over sliding window

Tianjin University of Technology

Phylogeny and zoogeography of the cyprinid genus Epalzeorhynchos Bleeker (Cyprinidae : Ostariophysi)

A total of 62 variable osteological and external characters was found among the five currently recognized species of Epalzeorhynchos. When the genera Crossocheilus and Paracrossocheilus are combined as the outgroup, only 30 of these characters can be polarized. This includes six autapomorphies. The remaining 24 polarized characters form a data matrix which yields a single, 26-step tree with a Consistency Index (CI) of 1 and a Retention Index (RI) of 1, The analysis was also performed on a combined dataset in which the 32 unpolarized characters (characters for which the combined outgroup was dimorphic) were added and coded as missing data (i.e., "?"), Analyzing this data matrix with all multistate characters ordered generates the same single most-parsimonious tree with a length of 63 steps, a CI of 0.98 and a RI of 0.97, When either Crossocheilus or Paracrossocheilus is used as the sole outgroup, the same single most-parsimonious tree is produced although the numbers of informative characters and some of the polarities differ. Evidence is presented to support the following hypotheses: (1) E, kalopterus + E, frenatus + E. bicolor + E. munensis form a monophyletic group; (2) E. frenatus + E, bicolor + E, munensis form a monophyletic group with E, kalopterus as its sister group; this speciation event is congruent with the predictions of vicariant speciation mode I; and (3) E. bicolor and E. munensis are sister groups, again congruent with vicariant speciation mode I, Evidence presented here also supports the zoogeographical hypothesis that the faunas of the Indochinese region and the Greater Sundas are more closely related to each other than either of them is to the lower Salween basin fauna and that the lower Mekong, Chao Phraya, and Mac Khlong basin faunas are more closely related to each other than any of them is to the Greater Sundas, In addition, the monophyly of Epalzeorhynchos is also preliminarily discussed by including either Paracrossocheilus or Crossocheilus in the ingroup. It is demonstrated that E. bicornis clusters with Paracrossocheilus when Paracrossocheilus is included in the ingroup. It seems likely that the taxonomic position of E. bicornis will be resolved as more fishes of the Crossocheilus group are included in future studies.

一种基于动态自适应数据窗口的模糊k-均值聚类缺失数据估算算法

完整性是数据质量的一个重要维度,由于数据本身固有的不确定性、采集的随机性及不准确性,导致现实应用中产生了大量具有如下特点的数据集:1)数据规模庞大;2)数据往往是不完整、不准确的.因此将大规模数据集分段到不同的数据窗口中处理是数据处理的重要方法,但缺失数据估算的相关研究大都忽视了数据集的特点和窗口的应用,而且回定大小的数据窗17容易造成算法的准确性和性能受窗口大小及窗口内数据值分布的影响.假设数据满足一定的领域相关的约束,首先提出了一种新的基于时间的动态自适应数据窗口检测算法,并基于此窗口提出了一种改进的模糊k-均值聚类算法来进行不完整数据的缺失数据估算.实验表明较之其他算法,不仅能更适应数据集的特点,具有较好的性能,而且能够保证准确性.

基于信息重建技术的地震信号处理方法研究

The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.