Bat algorithm is a new swarm intelligent optimization algorithm inspired by bat seeking behaviour. Due to the fast convergent speed, it has been applied to many areas successfully. In this paper, we incorporate bat al...
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This paper is concerned with the problem of tracking target with multiple sensors in the presence of unknown dynamic bias. A suboptimal adaptive two-stage Kalman filter(ATKF) is designed with two reduce-order filters ...
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ISBN:
(纸本)9781479947249
This paper is concerned with the problem of tracking target with multiple sensors in the presence of unknown dynamic bias. A suboptimal adaptive two-stage Kalman filter(ATKF) is designed with two reduce-order filters to estimate the target state and the dynamic bias in parallel when the bias model information is incomplete. Moreover, a distributed adaptive two-stage Kalman filter(DATKF) is developed for multi-sensor system based on the ATKF. The effectiveness of the ATKF and the DATKF are illustrated by the Monte Carlo simulation results.
To verify and evaluate the performance of a space robot controller,kinematics and dynamics of the system have to be formed beforehand for computer *** paper is devoted to develop a new kinematic notation for space rob...
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ISBN:
(纸本)9781479947249
To verify and evaluate the performance of a space robot controller,kinematics and dynamics of the system have to be formed beforehand for computer *** paper is devoted to develop a new kinematic notation for space robots and to come up with an open source of Matlab subroutines for the propose of obtaining the proper dynamics equations of space robots in symbolic forms *** the new kinematic notation,we will present the general form and two special *** is then demonstrated through an example the advantages such as flexible assignment of frames on space robots,being able to describe multi-DOF joint and achieve a consistent description for multi-arm space *** the second part,we adopt the Lagrangian Formulation for forming the procedures to automatically generate the dynamics equations of space robots in symbolic *** example is then provided to demonstrate the effectiveness of closed-loop simulation adopting the obtained symbolic equations.
Bacterial Foraging Optimization (BFO) is a novel intelligent optimization algorithm by simulating the bacterial foraging behaviours. In this paper, BFO is applied to solve coverage optimization problem which is one cr...
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DNA computing is a novel parallel computation paradigm. DNA, as the carrier of information and computing, is uncontrollable in biochemical reactions. There are many difficulties and limitations for the construction of...
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DNA computing is a novel parallel computation paradigm. DNA, as the carrier of information and computing, is uncontrollable in biochemical reactions. There are many difficulties and limitations for the construction of a molecular universal computer. Based on the Turing machine and sticker model, a new generalized turing model (GTM) independent of biotechnology and only with an ordinary single tape Turing machine was proposed. Validation tests on the model showed that it can be used to solve the integer programming problem in the polynomial time and has obvious advantages in both computation accuracy and simply coding.
The surface of the object is continuous and smooth. As one of the most popular methods, polygon meshes are extensively used in computer graphics. But it is difficult to achieve the sparse representation of polygon bas...
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ISBN:
(纸本)9781479942831
The surface of the object is continuous and smooth. As one of the most popular methods, polygon meshes are extensively used in computer graphics. But it is difficult to achieve the sparse representation of polygon based 3D model due to its raw and discrete characters. Thus, the compressive sensing based compression method cannot be applied on 3D model directly. However, the geometry images method provides a way for the sparse representation of 3D geometric data in advance of its regular structure. For the sparse representation, we first proposed a new normalization method for the geometric patches of the geometry image. Then, a over-complete dictionary based sparse representation method for normalized geometry image has been proposed. The measurement matrix was introduced to sampling the geometric data which can be sparse by over-complete dictionary. At the decoding, we can get the reconstructed geometric data by solving the optimization model. Our effectiveness results of this method are shown in the experimental section.
Crowd simulation has been widely used in virtual building evacuation, crowd behavior drilling, movie making, entertainment and many other fields. So far, it is still a difficult problem to synthesize realistic large-s...
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ISBN:
(纸本)9781479942831
Crowd simulation has been widely used in virtual building evacuation, crowd behavior drilling, movie making, entertainment and many other fields. So far, it is still a difficult problem to synthesize realistic large-scale crowd rendering with an interactive frame-rate in the real-time applications. Therefore, efficiency is a pivotal problem to resolve. This paper proposes a hybrid approach to guide crowd movements by constructing a navigation field and local collision avoidance simultaneously. Crowd can take use of navigation field which records the optimal path and local collision test keeping them off obstacles with modified vector to reach their desired destinations. With our proposed method, we build a simulation environment for crowd evacuation and realized the evacuation in assembly occupancies successfully with excellent rendering result and high efficiency in reasonable frame.
Because the existing computing models are mostly based on biological technology and lack versatility and accuracy, a new generalized molecular computation model (GCCM), which consisting a general Turing machine, writi...
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Because the existing computing models are mostly based on biological technology and lack versatility and accuracy, a new generalized molecular computation model (GCCM), which consisting a general Turing machine, writing tape, working tape and network, and a special topology mapping between the writing and the working tapes, was proposed. The model combines DNA computing and traditional computer model. Because of its big storage and high parallelism inherited from DNA computing, the model can solve NP complete problems by transforming space complexity to time complexity. In this paper, the definition and working principle of model were first introduced;then based on the model, a new algorithm of the set covering problem was put forth and its working process was shown. Finally, an instance was given to verify the ability of the algorithm to solve the set covering problem in polynomial time.
In order to deal with serious security threats of SQL injection to Web applications, this paper proposes a novel SQL-injection detection method based on genetic algorithm (GA). A unified description for characteristic...
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Dictionary learning for sparse representation has been an active topic in the field of image processing. Most existing dictionary learning schemes focus on the representation ability of the learned dictionary. However...
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ISBN:
(纸本)9781479957521
Dictionary learning for sparse representation has been an active topic in the field of image processing. Most existing dictionary learning schemes focus on the representation ability of the learned dictionary. However, according to the theory of compressive sensing, the mutual incoherence of the dictionary is of crucial role in the sparse coding. Thus incoherent dictionary is desirable to improve the performance of sparse representation based image restoration. In this paper, we propose a new incoherent dictionary learning model that minimizes the representation error and the mutual incoherence by incorporating the constraint of mutual incoherence into the dictionary update model. The optimal incoherent dictionary is achieved by seeking an optimization solution. An efficient algorithm is developed to solve the optimization problem iteratively. Experimental results on image denoising demonstrate that the proposed scheme achieves better recovery quality and converges faster than K-SVD while keeping lower computation complexity.
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