A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly foc...
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A directional filter algorithm for intensity synthetic aperture radar （SAR） image based on nonsubsampled contourlet transform （NSCT） and immune clonal selection （ICS） is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.
Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clona...
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Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.
This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also p...
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Because of noise and clutter, the infrared target detection even becomes more difficult. In this paper, we present an automatic seed selection method based on an improved mountain cluster algorithm to be employed in i...
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Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT)...
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Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT) is proposed, which provides better directionality and approximate shift invariance. By space mapping for the texture image, then complex Directionlet transform is applied to the mapped image, and the multiscale subband coefficient energy feature is used for texture classification. The experiments using texture images from Brodatz and real SAR images indicate the proposed method outperforms wavelets and Multiscale Geometric Analysis (MGA) approaches, the potential application to image analysis by Directionlet is thus proved.
A novel analytic approach is presented to study the population of excitatory and inhibitory spiking neurons in this paper. The evolution in time of the population dynamic equation is determined by a partial differenti...
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A novel analytic approach is presented to study the population of excitatory and inhibitory spiking neurons in this paper. The evolution in time of the population dynamic equation is determined by a partial differential equation. A new function is proposed to characterize the population of excitatory and inhibitory spiking neurons, which is different from the population density function discussed by most researchers. And a novel evolution equation, which is a nonhomogeneous parabolic type equation, is derived. From this, the stationary solution and the firing rate of the stationary states are given. Last, by the Fourier transform, the time dependent solution is also obtained. This method can be used to analyze the various dynamic behaviors of neuronal populations.
This paper focuses on the image segmentation, which is one of the key problems in medical imageprocessing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information...
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Instrument display panel is one of the most important parts of automobiles. Automatic detection of LED signal lamps is critical to ensure the reliability of automobile systems. In this paper, an automatic detection me...
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This paper proposes a novel model, the mission oriented model, for the problem of land-based satellite tracking telemetry and command (TT&C) resources scheduling. Compared to other models, the mission oriented mod...
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This paper proposes a novel model, the mission oriented model, for the problem of land-based satellite tracking telemetry and command (TT&C) resources scheduling. Compared to other models, the mission oriented model constrains a satellite to be tracked and commanded by only a ground station which can observe the satellite. Therefore, the proposed model makes it possible that scheduling algorithms schedule TT&C resources to complete more missions. Then it proposes the clonal selection land-based satellite TT&C resources scheduling algorithm (CS_STT&CRSA) based on the mission oriented model and proves its global convergence in theory. The algorithm adopts a matrix coding scheme, which depends on the start times of tracked and commanded orbits and the relationships between satellites and ground stations. The severe-constraint satisfaction operator which guarantees the individual satisfies severe constraints is proposed. When there are 5 geostationary satellites and 30, 40 or 50 low earth orbit and medium earth orbit (LEO&MEO) satellites, 10 different groups of tasks are generated respectively. Experimental results illustrate that the mission oriented model enables scheduling algorithms to make better use of TT&C resources and complete more missions and CS_TT&CRSA has more powerful ability of searching and solving constraints and is more stable.
A new algorithm for constrained multi-objective optimization is presented. The algorithm treats the constraints as an objective and the immune clone and immune memory mechanism are introduced. Therefore, the new algor...
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A new algorithm for constrained multi-objective optimization is presented. The algorithm treats the constraints as an objective and the immune clone and immune memory mechanism are introduced. Therefore, the new algorithm could find the Pareto-optimal solutions from the feasible region and the edge of the infeasible region, which assures both the convergence and diversity of the obtained solutions. Simulation results show that the new algorithm has much better performance in finding a much better spread of solutions, in maintaining a better uniformity of the solutions and in obtaining a better convergence.
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