In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi...
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In our study, support vector value contourlet transform is constructed by using support vector regression model and directional filter banks. The transform is then used to decompose source images at multi-scale, multi-direction and multi-resolution. After that, the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image. Finally, the super-resolved multi- spectral image and the panchromatic image are fused based on regions at different levels. Our experi- ments show that, the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image. The fused image preserves both high space resolution and spectrum information of multi-spectral image.
We first derive the asymptotic expansion of the bilinear finite volume element for the linear parabolic problem by employing the energy-embedded method on uniform grids, and then obtain a high accuracy combination poi...
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We first derive the asymptotic expansion of the bilinear finite volume element for the linear parabolic problem by employing the energy-embedded method on uniform grids, and then obtain a high accuracy combination pointwise formula of the derivatives for the finite volume element approximation based on the above asymptotic expansion. Furthermore, we prove that the approximate derivatives have the convergence rate of order two. Numerical experiments confirm the theoretical results.
Herein, a new identity recognition method of plantar pressure image (PPI) was investigated based on compressed sensing. During the process of identity recognition, the PPIs were collected with platform system in norma...
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ISBN:
(纸本)9781479925667
Herein, a new identity recognition method of plantar pressure image (PPI) was investigated based on compressed sensing. During the process of identity recognition, the PPIs were collected with platform system in normal walking speed. The sparse representation of PPI was then obtained according to the sparse basis (i.e., wavelet basis). Finally, measurement vectors were calculated by the Topelitz measurement matrix and the PPI was recognized by compressed sensing classifier. The results showed that the accuracy of identity recognition of PPI based on compressed sensing exceeded 97.76%, demonstrating the effectiveness and stability of the Topelitz-compressed sensing algorithm. Meanwhile, the method used in this study reduced the data storage amount and increased the real-time recognition during the PPI process.
In this paper, combining some special eigenvalue inequalities of matrix’s product and sum with the equivalent form of the continuous coupled algebraic Riccati equation (CCARE), we construct linear inequalities. Then,...
In this paper, combining some special eigenvalue inequalities of matrix’s product and sum with the equivalent form of the continuous coupled algebraic Riccati equation (CCARE), we construct linear inequalities. Then, in terms of the properties of M-matrix and its inverse matrix, through solving the derived linear inequalities, we offer new upper matrix bounds for the solution of the CCARE, which improve some of the recent results. Finally, we present a corresponding numerical example to show the effectiveness of the given results.
A Graph-based multi-hop cooperative MIMO transmission scheme (GM-MIMO) aimed at optimizing the network lifetime and saving energy for heterogeneous wireless sensor networks (WSN) is proposed. In GM-MIMO, clusters are ...
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In the present paper, a method for the real-time conversion of whisper to normal phonated speech in Chinese through a multiple excited linear prediction (MELP) analysis-by-synthesis codec is discussed. In the analysis...
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Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order st...
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Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. Tissue P systems are a class of the most investigated computing mod- els in the framework of membrane computing, especially in the aspect of efficiency. To generate an exponential resource in a polynomial time, cell separation is incorporated into such systems, thus obtaining so called tissue P systems with cell separation. In this work, we exploit the computational efficiency of this model and construct a uniform family of such tissue P systems for solving the independent set problem, a well-known NP-complete problem, by which an efficient so- lution can be obtained in polynomial time.
In order to solve the problem that the iterative method for Linear Projection- Based Non-negative Matrix Factorization (LPBNMF) is complex, a method, called Linear Projective Non-negative Matrix Factorization (LP-NMF)...
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Based on adaptive filtering and retinex method, this paper presents a novel algorithm for Enhancement of hand vein images. First of all, the principle of the near-infrared hand vein image acquisition is introduced. Se...
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Aiming at the low-rate and short-distance communication in existing temperature and humidity monitoring system, this paper designs a remote monitoring system based on 3G and Internet technology. This system consists o...
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