In this paper, a new change detection method based on image segmentation and fusion in multi-temporal SAR image is presented. The proposed fusion method exploits the conditional probability of difference image to two ...
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The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise. In this paper, a novel Bayesian nonlocal (BNL) means filter is derived, which is adapted ...
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As is well known that the quality of a digital image is affected by many factors, such as the distance between the acquisition system and the object, the acquisition environment conditions, and the resolution of the i...
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Based on the shift invariance and multidirectional expansion properties of Nonsubsampled Contourlet Transform, a new image segmentation combining hidden Markov trees model with Bayesian approaches is proposed here. Th...
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A new method for automated road extraction in remote sensing images is proposed based on Nonsubsampled Contourlet Transform (NSCT). Due to the advantages of multi-scale, multi-direction and translation invariance, NSC...
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In this paper, we present a new method of change detection in SAR images based on multiscale product of wavelet transform and PCA algorithm. This method applied multiscale product of wavelet transform, in order to avo...
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Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, his topic was also investigated in the framework of spiking neural systems. One of small universali...
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ISBN:
(纸本)9781424438655
Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, his topic was also investigated in the framework of spiking neural systems. One of small universality results is that a small weakly universal extended spiking neural P system with 12 neurons was constructed. In this paper, a new way is introduced for simulating register machines by spiking neural P systems, where only one neuron is used for all instructions of register machine;in this way, we can use less neurons to construct universal spiking neural system. Specifically, we give a smaller weakly universal spiking neural P system that uses extended rules and has only 9 neurons.
DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly may be scalable. In this paper, we mainly propose the algorithm of solving t...
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DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly may be scalable. In this paper, we mainly propose the algorithm of solving the subset-product problem based on DNA tile self-assembly, including constructing three small systems which are nondeterministic guess system, multiplication system and identification system, by which we can probabilistically get the solution of the subset-product problem. Our model can successfully perform the algorithm in polynomial time with optimal Theta(1) distinct tile types, parallely and at very low cost.
DNA encoding is crucial to successful DNA computation, which has been extensively researched in recent years. It is difficult to solve by the traditional optimization methods for DNA encoding as it has to meet simulta...
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DNA encoding is crucial to successful DNA computation, which has been extensively researched in recent years. It is difficult to solve by the traditional optimization methods for DNA encoding as it has to meet simultaneously several constraints, such as physical, chemical and logical constraints. In this paper, a novel quantum chaotic swarm evolutionary algorithm (QCSEA) is presented, and is first used to solve the DNA sequence optimization problem. By merging the particle swarm optimization and the chaotic search, the hybrid algorithm cannot only avoid the disadvantage of easily getting to the local optional solution in the later evolution period, but also keeps the rapid convergence performance. The simulation results demonstrate that the proposed quantum chaotic swarm evolutionary algorithm is valid and outperforms the genetic algorithm and conventional evolutionary algorithm for DNA encoding. (c) 2008 Elsevier Ltd. All rights reserved.
A time-varying Kalman filter is proposed to solve the problem of remote estimation with sensor scheduling and measurement loss. The statistical properties of the estimation error are studied. The expectation of the es...
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ISBN:
(纸本)9783642015120
A time-varying Kalman filter is proposed to solve the problem of remote estimation with sensor scheduling and measurement loss. The statistical properties of the estimation error are studied. The expectation of the estimation error covariance is proved to have upper and lower bounds. Convergence conditions and methods to calculate these bounds are also presented. The optimal sensor selection probability is found by using gradient search method. When the remote estimator schedules the transmission of sensors using optimal probability, the best estimation performance can be obtained. The validity of the proposed results are demonstrated by numerical examples.
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