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In this paper, we propose a new method for the design of a class of orthogonal filter banks with sparse coefficients in the minimax sense. We first formulate a design problem based on the minimization of the reweighted L1-norm of the filter bank coefficients subject to the perfect reconstruction (PR) and vanishing moments (VM)). As the PR constraint is nonconvex, we initialize the coefficients of...
In this paper, a secure compressive sensing (CS) based localization approach is proposed to cope with the attacked measurements from the malicious node by the residual error analysis. First, the intermediate target positions are estimated by the CS recovery method and then the residual errors are calculated as the indicator to identify each measurement. Second, according to the proposed residual error...
In this paper, we tackle the problem of common object (multiple classes) discovery from a set of input images, where we assume the presence of one object class in each image. This problem is, loosely speaking, unsupervised since we do not know a priori about the object type, location, and scale in each image. We observe that the general task of object class discovery in a fully unsupervised manner...
Considering complicated coupling process structure in the Business Process Management, this paper proposes a joint modeling strategy combining Petri net and Design Structure Matrix, and established the relevant process identify algorithm based on SDPSO to DSM modeling. Meanwhile Petri network graph model built by Anylogic software would be automatically transformed into DSM by Matlab software, and...
Dimension reduction (DR) algorithms are generally categorized into feature extraction and feature selection algorithms. In the past, few works have been done to contrast and unify the two algorithm categories. In this work, we introduce a matrix trace oriented optimization framework to provide a unifying view for both feature extraction and selection algorithms. We show that the unified view of DR...
Clustering is one of the important means of Intrusion detection. In order to overcome the disadvantages of fuzzy C-means algorithm, this paper presents a kind of improved fuzzy C-means algorithm (IFCM for short). IFCM algorithm reduces the infection of isolated point by means of weighting the degree of membership for objects to be clustered, and avoids the subjectivity in choosing the number of clustering...
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