To reduce the redundancy, a new integrated wavelet-based surfacelet transform(WBST) is proposed. The integrated WBST is constructed by combining the integrated 3D non-redundant wavelet with nonsubsampled directional filter banks. For 3D non-redundant wavelet transform, there are seven high frequency sub-bands and one high frequency sub-bands. Therefore, we design the integrated scheme with three high frequency sub-bands. In order to get the texture-spatial features, 3D local binary pattern (3D LBP) is used to describe the dynamic texture feature of low frequency sub-band. The mean and standard deviation of coefficients in each sub bands can be used as the high frequency features. Experiments show that the proposed algorithm using the integrated WBST outperforms the 3D WT.
The paper aims to study the problem of biclustering for gene expression data, which arises in the program of characterizing DNA clone libraries, especially in the oligonucleotide fingerprinting of ribosomal RNA genes method. Gene expression data are arranged in data matrices. The goal of biclustering is to find a submatrix, i.e., subset of rows and a subset of columns. If each element of a matrix is 0 or 1, biclustering is closely related to finding bicliques in a bipartite. The k-BVP (short for k biclique vertex partition problem) is to decide whether the vertices of a bipartite can be partitioned into k groups, and each group induce a biclique. 2-BVP can be solved in polynomial time, but it is an open problem whether or not k-BVP is in P for all k3. On the one hand, present an O(2|V|-3) algorithm to decide whether or not a bipartite graph contains a 3 biclique vertex partition. On the other hand, give an algorithm to produce simulation data. The testing results show that the algorithm can find a 3-BVP of a bipartite if there exist a 3-BVP in the bipartite.
Biclustering has been extensively studied in many fields such as data mining, e-commerce, computational biology, information security, etc. Problems of finding bicliques in bipartite, which are variants of biclustering, have received much attention in recent years due to its importance for biclustering. The k-biclique vertex partition problem proposed by Bein et al. is one of finding bicliques problems in bipartite. Its aim is to find k bicliques (kk) such that each vertex of the bipartite occurs in exactly one member of these bicliques. First, we give a sufficient condition of the k-biclique vertex partition problem. Moreover, we present an exact algorithm for finding k-biclique vertex partitions of a bipartite. Finally, we propose a method to generate simulated datasets used to test the algorithm. Experimental results on simulated datasets show that the algorithm can find k-biclique vertex partitions of a bipartite with relatively fast speed.
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