Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the ...
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Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the minimal Roesser model realization problem for a class of 2D systems which does not belong to the clarified categories. As one of the main results, a constructive realization procedure is first proposed. Based on the proposed procedure, sufficient conditions and explicit construction for minimal realizations of the considered 2D systems are shown. In addition, possible variations and applications of the obtained results are discussed and illustrative examples are presented.
The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a...
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To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform ...
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To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.
Electroencephalography (EEG) is widely used in the field of neural engineering. EEG signals can describe the brain activities while the subjects with para/tetraplegia perform movement with their limbs. This paper revi...
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A robust non-linear feedback control strategy combined with neural network (NN) estimator is presented, for the non-linear model of bank-to-turn (BTT) missile with modelling uncertainties. The non-linearities in the m...
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A robust non-linear feedback control strategy combined with neural network (NN) estimator is presented, for the non-linear model of bank-to-turn (BTT) missile with modelling uncertainties. The non-linearities in the missile dynamics are taken into account, including coupling items between three channels. Standard feedback linearisation is implemented to linearise and decouple the nominal system. In the presence of unknown bounded uncertainties, the performance will deteriorate because the precise model cannot be obtained. Then, linear matrix inequality (LMI) based guaranteed cost control (GCC) is adopted to solve the robust control problem for the linearised uncertain models. Further, adaptive neural network estimators, which use Lyapunov based tuning rules, are integrated in the control strategy to eliminate the effect of high-order uncertain terms. Simulation results on a specified BTT missile model are provided to demonstrate the feasibility and effectiveness of the proposed approach, which achieves more improved tracking performance comparing with conventional method.
The separation property of Liquid State Machine (LSM) is a key for its power of computing, but the weights and delays of the inter-connections in the spiking neural circuit are usually randomly created and kept unchan...
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ISBN:
(纸本)9783642015120
The separation property of Liquid State Machine (LSM) is a key for its power of computing, but the weights and delays of the inter-connections in the spiking neural circuit are usually randomly created and kept unchanged. which hinders the performance of the LSM greatly. In this paper. particle swarm optimization (PSO) was applied to optimize the weights and delays of the circuit so as to enhance the separation property of the LSM. Separation of random spike trains and Fisheriris data-set classification experiments are done by the optimized circuit. Demonstration examples show that the PSO can enlarge the separation property of the circuit greatly compared to the normal Hebbian-learning algorithm and enhance the computing ability of LSM.
Electroencephalogram (EEG) recordings during motor imagery tasks are often used as input signals for brain-computer interfaces (BCls). We analyze the EEG signals with Daubechies order 4 (db4) wavelets in 10 Hz and 21 ...
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ISBN:
(纸本)9783642015090
Electroencephalogram (EEG) recordings during motor imagery tasks are often used as input signals for brain-computer interfaces (BCls). We analyze the EEG signals with Daubechies order 4 (db4) wavelets in 10 Hz and 21 Hz at C3 channel, and in 10 Hz and 20 Hz at C4 channel, for these frequencies are prominent in discrimination of left and right motor imagery tasks according to EEG frequency spectral. We apply the improved support vector machines (SVMs) for classifying motor imagery tasks. First, a SVM is trained on all the training samples, then removes the support vectors which contribute less to the decision function from the training samples. finally the SVM is re-trained on the remaining, samples. The classification error rate of the presented approach was as low its 9.29 % and the mutual information could be 0.7 above based on the Graz BCI 2003 data set.
In this study, the sliding mode approach is applied to the tracking control problem of a planar arm manipulator system driven by a new type of actuator, which comprises a pneumatic muscle (PM) and a torsion spring. Un...
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ISBN:
(纸本)9781424447749
In this study, the sliding mode approach is applied to the tracking control problem of a planar arm manipulator system driven by a new type of actuator, which comprises a pneumatic muscle (PM) and a torsion spring. Unlike the traditional agonist/antagonist pneumatic muscle actuator, the PM is arranged in place of bicep and the torsion spring provides opposing torque in the presented actuator. The dynamic model is derived for this system and a sliding mode controller is designed to make the joint angle track a desired trajectory within a guaranteed accuracy even there are modeling uncertainties. A selection method is also proposed to obtain appropriate spring coefficient, which plays an important role in the tracking control task. The effectiveness of the proposed method is confirmed by simulations. The differences between the control results of using our new actuator and that of using the traditional pneumatic muscle actuator in opposing pair configuration are also compared.
This paper studies the tracking problem for a class of stochastic nonlinear interconnected systems with unknown parameters involved. By employing the stochastic Lyapunov-like theorem and the backstepping design techni...
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ISBN:
(纸本)9781424427239
This paper studies the tracking problem for a class of stochastic nonlinear interconnected systems with unknown parameters involved. By employing the stochastic Lyapunov-like theorem and the backstepping design technique, a decentralized state-feedback controller and parameter adaptive law are developed. The output of the closed-loop system is proven to follow the desired trajectory asymptotically in probability.
In this paper, an approach for detecting bridges over water bodies from high resolution SAR images is presented. It consists of two steps: water extraction and bridge detection. A method based on porosity combined wit...
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