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Mean shift algorithm is a statistics iterative algorithm which is widely used, its increment (namely mean shift vector) of iterative point in each iteration step changes adaptively. This paper presents an extensional mean shift vector, and proves convergence of mean shift algorithm which using the extensional mean shift vector. In addition, we did an experiment - using mean shift algorithm to solve...
This paper proposes a novel scheme that we call the opposition based comprehensive learning particle swarm optimizers (OCLPSO), which employs opposition based learning (OBL) for population initialization and also for exemplar selecting. This scheme enables the swarm to explore and exploit with the more diversity and not to be premature convergence. Experiments were conducted on benchmark functions...
In this paper, the concept of the frequently covered points (FCP) and the infrequently covered points (ICP) is presented. By means of the cutpoints sieve method, we can rapidly pick out the corresponding cutpoints of ICP, namely preferred cutpoints, from all pending cutpoints of interval attributes. And then, only preferred cutpoints are used for computing information entropy of partition (IEP). Finally,...
Parameters setting is an important problem of evolution algorithms, include differential evolution algorithm. It has an effect on the performance of evolution algorithms. Although there is only three control parameters in differential evolution (DE) algorithm, the parameters setting is also a difficult problem. Self-adaptation is highly beneficial for adjusting the control parameters, especially when...
This paper is aimed to present a genetic algorithm focusing on the sexual selection used the Pareto based approach for solving multi-objective optimization problems. It uses a concept of sexual selection with different types of gender and mutation rates based on the sex to produce offspring. Its performance was evaluated by the well-known benchmark functions as well as also tested with a networking...
The single-source shortest path problem (SSSP), known as the basis of many application areas, is a fundamental matter in graph theory. In this paper, a new efficient algorithm named Li-Qi (LQ) is proposed for SSSP to find a simple path of minimum total weights from a designated source vertex to each vertex. The algorithm is based on the ideas of the queue and the relaxation, The main differences between...
Based on the study of patterns used in many fast algorithms for the block-matching motion estimation (BMME), a new search pattern, LP (line search pattern), was introduced in this paper. LP is also a simplified square search pattern as TP(Triangle search Pattern). By combing LP with DP(diamond search pattern), a fast BMA (BMME Algorithm), DLS (diamond-line search), was also proposed in this paper...
It is well known that H.264/AVC has great advantage of coding efficiency compared with the successful prior coding standards and it can save about 50% bit-rate under the same reconstructed picture quality. But the complexity of H.264/AVC encoder is also very high and it limits the application of H.264/AVC in the domain of real time video communication. Based on some observations in the experiments,...
Floorplanning is an important problem in the very large integrated circuit (VLSI) design automation. It??s an NP-hard combinatorial optimization problem. The particle swarm optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem due to its continuous characteristic. In...
Attributions including the type of minutiae, the curvature of ridge, the length ratio of 2 line segments of ridge and the relative topological relationship among minutiae and ridges were used in partial and/or nonlinear distorted fingerprint matching. Three kinds of criterions were defined to describe the pattern of fingerprint. Fingerprint was matched in steps according to the criterions consist...
One of the key factors that limit support vector machines (SVMs) application in large sample problems is that the large-scale quadratic programming (QP) that arises from SVMs training cannot be easily solved via standard QP technique. The sequential minimal optimization (SMO) is current one of the major methods for solving SVMs. This method, to a certain extent, can decrease the degree of difficulty...
Anaphora is a common phenomenon in a natural language. It plays a large role in the coherence of a text and is a subject of active study in computational linguistics. This paper puts forward several anaphora resolution algorithms for the personal pronouns of written Chinese based on Focus-set Theory and DRT. The strength of our methods lies in the emphasis on the construction of Focus-set and in the...
Reverse nearest neighbor (RNN) query now is one of the important queries in spatial database and data mining. Reverse k nearest neighbor(RkNN) is the extendibility of RNN. Given a set V of objects and a query object q, an RkNN query returns a subset of V such that each element of the subset has q as its kNN member according to a certain similarity metric. Early methods pre-compute NN of each data...
Attribute reduction is an important issue of data mining. In this paper an incremental reduct algorithm is proposed for incomplete decision tables. A reduct definition is firstly presented. And then based on the concept of generalized decision the different cases caused by adding a new object to an incomplete decision table are deeply analyzed and some important conclusions are proved by theorems...
DNA sequences are formed by nucleotides A;C; G; T. Often, a particular word called motif can occur in many sequences of a group. There has been an algorithm to find both the frequent and the maximal motif in the DNA sequences, but it has some disadvantages. Such as the time and place cost is very high. In the paper, we build a tree based on the motif length to improve it, and implement a small system...
One of the key questions in algebraic attacks is how to effectively reduce the degree of the function. Based on the algebraic attack, this paper presents a new algorithm of attack - chosen IV algebraic attack, which can reduce the function??s degree by choosing appropriate IV. Using this algorithm, we analyze the One.Fivium, the predigesting form of Trivium. we can get 70 key bits, and the length...
In this paper, an improved method is proposed based on AntTree clustering algorithm to deal with MRI image. This algorithm uses a new tree-structure model to accelerate the calculation and combines greedy algorithm to update the cluster centre. Compared with K-means and FCM algorithms, the results in the experiment show that the improved AntTree clustering algorithm is a better method in image segmentation...
In this paper, we have proposed a novel algorithm for fingerprint segmentation. Firstly, we originally use the method of gradient projection to eliminate those background regions which have smaller gray contrast, and then obtain the approximate foreground region of the fingerprint image. In addition, we adopt the gradient coherence criteria to exclude the regions which contain irregular stains and...
The connection analysis of pipeline network is one of the most important functions of pipeline spatial analysis. In the abstract, that problem is the minimum spanning tree calculation problem -- the combination optimization problem. Traditional method can get only one tree concerning one factor. In this paper, genetic algorithm is used to solve minimum spanning tree to get a group solution, from which...
In order to improve the global ability of basic ACA(ant colony algorithm), a novel ACA algorithm which is based on adaptively adjusting pheromone decay parameter has been proposed, and it has been proved that for a sufficiently large number of iterations, the probability of finding the global best solution tends to 1. The simulations for TSP problem show that the improved ACA can find better routes...
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