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According to existing have defects discernibility matrix, and the attribute reduction algorithm for attribute reduction algorithm of complex process. This paper made part of optimization, based on the condition attributes classify the grouping generated representative data to simplify the discernibility matrix, and the order of the discernibility matrix, and the complexity of the attribute reduction...
Recently, distance metric learning has been received an increasing attention and found as a powerful approach for semi-supervised learning tasks. In the last few years, several methods have been proposed for metric learning when must-link and/or cannot-link constraints as supervisory information are available. Although many of these methods learn global Mahalanobis metrics, some recently introduced...
In this letter, we introduce a novel method for constructing large size generalized Welch bound equality (GWBE) matrices. This method can also be used for the construction of large WBE matrices. The advantage of this method is its low complexity for constructing large size matrices and low computational complexity using maximum likelihood (ML) decoders for a subclass of these codes.
Edge contraction simplification based on DEM terrain algorithm is proposed as a new terrain simplification algorithm which is based on DEM terrain data characteristics. The algorithm introduces the gradient of triangle, and combines with gradient and the length of edges as weight of the vertex to represent the importance of a vertex. By using the vertex weight, we can constrain the region being affected...
Abstract-Symmetric Loewner-type matrix has broad applications in natural sciences and engineering technologies. Many of the issues are summarized for the sake of symmetric Loewner (type) matrix and its correlation matrix algebraic problem. We present a new fast algorithm of Moore-Penrose inverse for an m??n symmetric Loewner-type matrix with full column rank by forming a special block matrix and studying...
In this paper, a combined MLFMA-ACA approach is presented, which is applicable to three dimensional scattering problems of widely varying electrical sizes with complexity and fine structure. The classic MLFMA suffers breakdown at low frequencies, while ACA algorithm becomes less efficient than MLFMA at high frequencies. The presented algorithm combines these two methods to achieve stability at all...
Wet paper codes are an essential tool for communication with non-shared selection channels. Inspired by the recent ZZW construction for matrix embedding, we propose a novel wet paper coding scheme with high embedding efficiency. The performance is analyzed under the assumption that wet cover elements form an i.i.d. Bernoulli sequence. Attention is paid to implementation details to minimize capacity...
Discernibility matrix method is an important method to design algorithm for computing the core based on information entropy. In this method, the core is found by discovering all discernibility elements of discernibility matrix. So this method is very time consuming. To improve the efficient of computing the core based on information entropy, the core of the simplified decision which is the same as...
Rough set theory is emerging as a powerful tool for reasoning about data. Attribute reduction is one of important topics in the research on the rough set theory. The classical rough set theory based on equivalence relation has made a great progress, while the equivalence relation is too harsh to meet and is extended to tolerance relation in real world. It is important to investigate rough computational...
Analysis of gene expression data includes classification of the data into groups and subgroups based on similar expression patterns. Standard clustering methods for the analysis of gene expression data only identifies the global models while missing the local expression patterns. In order to identify the missed patterns biclustering approach has been introduced. Various biclustering algorithms have...
Rough set theory is emerging as a powerful toll for reasoning about data. Attribute reduction is one of important topics in the research on the rough set theory. Heuristic, discernibility matrix and matrix method are three usually methods for designing attribute reduction algorithm in attribute reduction based on rough set. Some researchers use matrix method to design attribute reduction algorithm...
This research proposes efficient calculation methods for the transition matrices in discrete event systems, where the adjacency matrices are represented by directed acyclic graphs. The essence of the research focuses on obtaining the Kleene Star of an adjacency matrix. Previous studies have proposed methods for calculating the longest paths focusing on destination nodes. However, in these methods...
It is well known that the circulant matrices are very important and special matrix. In recent years, various type of circulant matrices have been applied in such as signal dealing and oil exploration, and so on. In this paper, motivated by [Shen Guangxing (2004)], we give a fast algorithm for evaluating the m-th power of level-k(r1, r2, ??????, rk)-circulant matrices of type (n1, n2, ??????, nk)....
The attribute reduction algorithms designed by the method of discernibility matrix have lots of repeat and unnecessary elements in the discernibility matrix, which not only cost a mass of memory space, but also waste plenty of computing time for calculating attribute reduction. In order to improve the efficiency of such attribute reduction algorithm, by considering the idea of FP tree, a novel data...
This research implements an efficient solver for scheduling problems in a class of repetitive discrete event systems using a CELL/B.E. (cell broadband engine). The essence of this involves efficiently computing the transition matrix of a system whose precedence constraints regarding the execution sequence of jobs can be described by a weighted DAG (directed acyclic graph). This means solving the longest...
A rough set theory is a new mathematical tool to deal with uncertainty and vagueness of decision system, and the Computation of a Core is one of the most important problems of rough set. This paper introduces an improved algorithm based on discernibility matrix by Yang, and proposes an incremental updating algorithm for Core Computation. The space and time complexity of the new algorithm are cut down...
The research on innovation has become an important trend from the perspectives of system and its relative system theories. According to knowledge about enterprise innovation and self-organization theory, innovations include culture innovation, knowledge innovation, institution innovation, technology innovation, management innovation, and so on. Innovation integration is defined as a dynamic innovation...
In this paper, we present a new forced convergence decoding scheme for LDPC codes. We remove the early detected variable nodes from the Tanner graph and thus the parity matrix shrinks iteration by iteration and the decoding complexity can be reduced. When the parity check matrix shrinks to zero before the maximum iteration, we get a chance to detect the wrong deletion and, for the decodable codewords,...
As a practical method for knowledge reduction, discernible matrix (DM) has been widely used in practice. However, due to the high cost of constructing and reducing of a matrix, the efficiency of this method falls far short of people's demands. In order to decrease the cost of knowledge reduction based on the ideas of set theory, the paper presents a new approach, which is called the minimum discernible...
Abstract-Non-orthogonal Spectrally Efficient Frequency Division Multiplexing (SEFDM) signals of a small dimensionality can be optimally detected using the Sphere Decoder (SD) algorithm. However, the employment of such detectors is restricted by two factors; the ill-conditioning of the SEFDM projections matrix in the system linear statistical model and the sensitivity of the SD complexity to noise...
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