For uncertain Takagi-Sugeno (T-S) fuzzy systems with time-domain constraints on control inputs and states, a robust control scheme is proposed. Sufficient condition for achieving a given H-infinity performance level f...
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For uncertain Takagi-Sugeno (T-S) fuzzy systems with time-domain constraints on control inputs and states, a robust control scheme is proposed. Sufficient condition for achieving a given H-infinity performance level for the uncertain T-S fuzzy systems is given. Under the bound assumption of the disturbance energy, an ellipsoid containing all perturbed trajectories is found, and then, the time-domain hard constraints are translated into constraints in linear matrix inequalities (LMI) by using S-Procesure and double-ellipsoid method. This multi-objective design is eventually brought into solving an optimization problem with LMI constraints. Simulation of the application to an inverted pendulum is performed;and results are discussed.
For improving accuracy of optical flow computation, we propose a new method to compute optical flow from both gray and color information. First, the Gauss filter is used to pre-filter the color image sequence. Then op...
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ISBN:
(纸本)9781424446995
For improving accuracy of optical flow computation, we propose a new method to compute optical flow from both gray and color information. First, the Gauss filter is used to pre-filter the color image sequence. Then optical flow recovery is based on the method of neighborhood least squares using brightness information. And the weight coefficients of local neighborhood are determined by U and V channels in LUV color space. Finally, the optical flow result is filtered by median filter. The experiment results show that the proposed method produces dense optical flow field and accuracy of the results can also be improved.
It is difficult to build an accurate model using the traditional predictive control algorithm for a nonlinear system. Because of the nonlinearity, time variation, the control quality is not ideal. A nonlinear predicti...
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In recent years, because of the birthrate declining and the elderly peoplepsilas population growing, the lack of doctors and the increase of the medical cost is becoming a big problem. One of solution for this problem...
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ISBN:
(纸本)9781424435692
In recent years, because of the birthrate declining and the elderly peoplepsilas population growing, the lack of doctors and the increase of the medical cost is becoming a big problem. One of solution for this problem is to prevent the humans from diseases in order to reduce the medical cost (e.g. by using the hospital as few times as possible). In this research, we have developed a wearable vital sensor which can be used anywhere without disrupting the everyday life of the patient. Furthermore, we have implemented a ubiquitous health monitoring system, which can confirm and share the sensor information received from a cellular phone attached to the wearable vital sensor immediately through the browser. This system can also send emergency report based on sensor information to the family and the doctor. In addition, we verified the system effectiveness by evaluating the implemented system.
An 3D measurement scheme by combining Gray code with Trapezoidal phase-shift is presented. The scheme computes the relative intensity ratios in a Trapezoidal phase-shift period using Trapezoidal phase-shift pattern. C...
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An 3D measurement scheme by combining Gray code with Trapezoidal phase-shift is presented. The scheme computes the relative intensity ratios in a Trapezoidal phase-shift period using Trapezoidal phase-shift pattern. Combining the Trapezoidal phase-shift with Gray code corresponding to sampling point, and the absolute intensity ratio of sampling point is determined. Then, 3D measurement is realized using projection geometry matrix model. Encoding and decoding principles by combining Gray code with Trapezoidal phase-shift are presented;period dislocation between Gray code and Trapezoidal phase-shift in course of decoding is analyzed, which could be corrected by judging the consistency between Gray code value increasing and phase mutation of adjacent pixels. Finally, simulation and real system were experimented. The experimental results indicate that relative measurement error of simulation system is about 0.0325% and that of real system is less than 4.0329%.
This paper uses an estimated noise transfer function to filter the input-output data and presents a filtering based recursive least squares algorithm for ARMAX models. Through the data filtering, we obtain two identif...
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This paper uses an estimated noise transfer function to filter the input-output data and presents a filtering based recursive least squares algorithm for ARMAX models. Through the data filtering, we obtain two identification models, one including the parameters of the system model, and the other including the parameters of the noise model. Thus, the recursive least squares method can estimate the parameters of these two identification models, respectively, by replacing unmeasurable noise terms in the information vectors with their estimates. The proposed F-RLS algorithm has high computational efficiency because the dimensions of its covariance matrices become small and can generate more accurate parameter estimation compared with other existing algorithms.
Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is...
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Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is maximized. Labeled data, however, often consume much time and are expensive to obtain, as they require the efforts of human annotators. In order to cope with the problem of effectively combining unlabeled data with labeled data to find the embedding transformation, we propose a novel method, called subspace semi-supervised Fisher discriminant analysis (SSFDA), for semi-supervised dimensionality reduction. SSFDA aims to find an embedding transformation that respects the discriminant structure inferred from the labeled data and the intrinsic geometrical structure inferred from both the labeled and unlabeled data. We also show that SSFDA can be extended to nonlinear dimensionality reduction scenarios by applying the kernel trick. The experimental results on face recognition demonstrate the effectiveness of our proposed algorithm.
One kind of combustible gas alarms based on industrial Ethernet was designed to prevent the gas leakage in industrial production sites, The alarm adopted the high performance microprocessor LPC2214 as the main chip. T...
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One kind of combustible gas alarms based on industrial Ethernet was designed to prevent the gas leakage in industrial production sites, The alarm adopted the high performance microprocessor LPC2214 as the main chip. The embedded operating system μC/OS-Ⅱand TCP/IP protocol stack uIP running on LPC2214 constitute a development platform of application of the combustible gas alarm, The test shows that it can automatically and continuously detect combustible gas in industrial production sites in several positions;it can give out sound-light alarm and take protective measures immediately against the gas leakage; and it can send the detected data to PC through the Ethernet interface to realize the remote detection. The designed project provides a reference to design industrial devices based on industrial Ethernet
Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is...
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Fisher discriminant analysis (FDA) is a popular method for supervised dimensionality reduction. FDA seeks for an embedding transformation such that the ratio of the between-class scatter to the within-class scatter is maximized. Labeled data, however, often consume much time and are expensive to obtain, as they require the efforts of human annotators. In order to cope with the problem of effectively combining unlabeled data with labeled data to find the embedding transformation, we propose a novel method, called subspace semi-supervised Fisher discriminant analysis (SSFDA), for semi-supervised dimensionality reduction. SSFDA aims to find an embedding transformation that respects the discriminant structure inferred from the labeled data and the intrinsic geometrical structure inferred from both the labeled and unlabeled data. We also show that SSFDA can be extended to nonlinear dimensionality reduction scenarios by applying the kernel trick. The experimental results on face recognition demonstrate the effectiveness of our proposed algorithm.
Efficiency and fairness are two crucial issues to be considered for resource alloca- tion in multi-user wireless networks. Based on the joint optimization of physical layer and data link layer, an optimization model i...
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Efficiency and fairness are two crucial issues to be considered for resource alloca- tion in multi-user wireless networks. Based on the joint optimization of physical layer and data link layer, an optimization model is derived to achieve efficient and fair downlink data scheduling in multi-user OFDM wireless networks by maximizing the total utility function with respect to the average waiting time of user queue. A dynamic sub-carrier allocation algorithm (DSAA) based on the optimization model is proposed in order to obtain the maximization of the total scheduling utility. Effi- ciency is improved by combining DSAA with time scale interference predictor (TSIP) which at large time scales predict ON/OFF period of user data with temporal corre- lation structure across multiple time scales in multi-user interference environment. Simulation results verify the efficiency and fairness of the scheme.
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