A real time and autonomous obstacle avoidance method based on rules for mobile robots was presented. Wall- along algorithm was dynamically implemented in unknown environment without collision. The results show that th...
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A real time and autonomous obstacle avoidance method based on rules for mobile robots was presented. Wall- along algorithm was dynamically implemented in unknown environment without collision. The results show that this algorithm is time saving and no disturbance. The approaches proposed has effectiveness and reliability.
Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling....
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Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.
The interval models of uncertain plants are frequently used in the field of robust control. In this paper, a novel interval model identification method based on linear programming is proposed. By certain prepossessing...
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This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by em...
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This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by employing random series with Bernoulli distributions. A sufficient condition for robust stability with H_(infinity) constraints is derived for the filtering error system. The robust filter is designed in terms of the feasibility of a linear matrix inequality (LMI). The numerical examples are provided to show the effectiveness of the data transmission model and the proposed filtering method.
In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a biswarm particle swarm optimization with cooperative coevolution (BPSO-CC). BPSO-CC adopts two swarms to go on the s...
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ISBN:
(纸本)9780769542027
In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a biswarm particle swarm optimization with cooperative coevolution (BPSO-CC). BPSO-CC adopts two swarms to go on the search, the first swarm is designated to conduct the coarse search in the whole space, while the second swarm is generated periodically surround the first swarm and designated to make the fine search in the local search area around the first swarm. With the same aim to find out the global optimum, the two swarms go on their search in parallel. at the same time, they keep the cooperative co-evolution through sharing and exchanging the valid information, which can make them search in correct direct and improve the convergent efficiency of PSO validly. The proposed BPSO-CC has been applied to solve some benchmark functions with large scales, the simulation results demonstrate that BPSO-CC is a robust technique for complex optimizations and performs better than SPSO, not only in the convergence precision but also in the efficiency. 2010 IEEE.
In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a bi-swarm particle swarm optimization with cooperative co-evolution (BPSO-CQ. BPSO-CC adopts two swarms to go on the ...
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In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a bi-swarm particle swarm optimization with cooperative co-evolution (BPSO-CQ. BPSO-CC adopts two swarms to go on the search, the first swarm is designated to conduct the coarse search in the whole space, while the second swarm is generated periodically surround the first swarm and designated to make the Gne search in the local search area around the first swarm. With the same aim to find out the global optimum, the two swarms go on their search in parallel, at the same time, they keep the cooperative co-evolution through sharing and exchanging the valid information, which can make them search in correct direct and improve the convergent efficiency of PSO validly. The proposed BPSO-CC has been applied to solve some benchmark functions with large scales, the simulation results demonstrate that BPSO-CC is a robust technique for complex optimizations and performs better than SPSO, not only in the convergence precision but also in the efficiency.
The sampling storage method which used in the current data stream could not respond data tendency effectively. For the problem, this paper presents a new processing method based on curve fitting. A weighted least-squa...
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The paper presents a theorem to show the relationship between the parameters of the Moving Average (MA) process and those of its inversed process. The theorem can be used for the parameter identification of the MA pro...
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ISBN:
(纸本)9787894631046
The paper presents a theorem to show the relationship between the parameters of the Moving Average (MA) process and those of its inversed process. The theorem can be used for the parameter identification of the MA process. It is further shown in this paper that the parameter identification of autoregressive moving average with exogenous variable model (ARMAX), based on the identification of its MA part, can be easily achieved. The approach, at first, achieves the identification of the ARX part by directly using least-square estimations to find out a straightforward relationship between estimated parameters and observed data. Then, the inversed model of the MA part is identified in a similar way. Finally, the noise variance can be computed by using identified MA parameters. Numerical simulations validate the effectiveness and efficiency of the proposed approach.
A novel algorithm to solve the target tracking and formation control problem in multi-agent systems is proposed in the present work, which combines centroidal Voronoi tessellations (CVT) with consensus strategy. The a...
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ISBN:
(纸本)9787894631046
A novel algorithm to solve the target tracking and formation control problem in multi-agent systems is proposed in the present work, which combines centroidal Voronoi tessellations (CVT) with consensus strategy. The algorithm utilizes the connection information among robots to further reduce the system cost function on the basis of CVT configuration. The work load among robots can be averaged by the consensus strategy thus the tracking and formation task can be achieved. The method configures the robots on to local optimal solution which minimize the sensing error. Simulations validated the proposed approach. Comparison is drawn between the pure CVT algorithm and the method with consensus strategy.
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matri...
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ISBN:
(纸本)9787894631046
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matrix inequalities (LMIs), guarantee the synchronized states to be global asymptotically stable. In addition, an interesting conclusion is reached that the chaotic synchronization in the coupled whole 3N-dimensional networks can be converted into that of 3-dimensional space.
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