This paper proposes a Context Based Emotional controller (CBEC) to Thyrislor controlled Series Capacitor (TCSC), which might have a significant impact on power system dynamics. The role of a CBEC is to control a firin...
详细信息
This paper proposes a Context Based Emotional controller (CBEC) to Thyrislor controlled Series Capacitor (TCSC), which might have a significant impact on power system dynamics. The role of a CBEC is to control a firing angle of the TCSC. In this case, the CBEC is used for damping the low frequency oscillations caused by disturbances such 3s a sudden change of small or large loads or an outage in the generators or transmission lines. To evaluate the usefulness of the proposed method, we compare the response of CBEC with fumy PI) controller. The simulation results show that our method has the better control performance than fuzzy PD controller.
UTMAC is an object-oriented C++ class library, developed for design, implementation and simulation of multi-agent controllers. Using UTMAC, the control problem under analysis should be decomposed into several partial ...
详细信息
UTMAC is an object-oriented C++ class library, developed for design, implementation and simulation of multi-agent controllers. Using UTMAC, the control problem under analysis should be decomposed into several partial sub-problems to be solved by controller-agents, which can be implemented as reusable entities. UTMAC uses a non-centralized simulation scheme in which cash agent simulates itself. In this paper the structure of UTMAC is explored and design of a simple reusable multi-agent controller is provided to illustrate the work and show the convenience of design and implementation.
A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time seri...
详细信息
A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data
A unified and general framework is presented for H/sub /spl infin// control of mixed continuous-time and discrete-time time-varying (periodic) systems. Using the delta operator, a close relationship is shown between t...
详细信息
A unified and general framework is presented for H/sub /spl infin// control of mixed continuous-time and discrete-time time-varying (periodic) systems. Using the delta operator, a close relationship is shown between the continuous- and discrete-time solutions. No assumptions are made on certain system matrices being zero or normalized, which makes the approach general and easy to apply. A combined continuous/discrete-time lifting procedure is shown to be useful, especially for ill-conditioned systems. This procedure together with the delta formalism results in a numerically robust design method concerning both short and long sampling periods for systems with W-conditioned dynamics, including widely spread eigenvalues.
A procedure for H/sub /spl infin// optimization of low order controllers for discrete-time and sampled-data systems is presented in this paper. Generally, low order H/sub /spl infin// controllers may be achieved by so...
详细信息
A procedure for H/sub /spl infin// optimization of low order controllers for discrete-time and sampled-data systems is presented in this paper. Generally, low order H/sub /spl infin// controllers may be achieved by solving bilinear matrix inequalities (BMIs). In this paper an iterative alternation between two LMIs gives a suboptimal solution. To avoid local minima in this search the initial controller is obtained by a frequency weighted controller reduction scheme, where the closed loop properties of a full order controller is taken into account. A minimal number of parameters in the state space realization of the controller also reduces the complexity and improves numerical robustness. The complete presentation is based on delta operator models, which shows a close relationship between the continuous- and discrete-time solutions. The sensitivity of the ordinary discrete-time shift operator LMI formulation to small sampling periods is also analyzed.
This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects,...
详细信息
The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dime...
详细信息
The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dimensional grid structure with a growing self-organizing mechanism. In the learning phase, a growing SOM is trained and the growing cell structure is used as the baseline framework. In the ordination phase, the new projection method is used to map the input vector so that the input data is mapped to the structure of the SOM without having to plot the weight values, resulting in easy visualization of the data. The projection method is demonstrated on four different data sets, including a 118 patent data set and a 399 checical abstract data set related to polymer cements, with promising results and a significantly reduced network size.
A heuristic, automatic facial feature extraction approach is presented in this paper. The method is based on the edge density distribution of the image, containing non-occluded, nearly frontal view of one or more face...
详细信息
A heuristic, automatic facial feature extraction approach is presented in this paper. The method is based on the edge density distribution of the image, containing non-occluded, nearly frontal view of one or more faces. In the preprocessing stage, a face is approximated to an ellipse, and genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, genetic algorithm is applied to extract the facial features, such as the eyes (with eyebrows), nose and mouth, in the predefined subregions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of complex backgrounds, certain amount of artificial noise and of multi-face oriented with angles. This preliminary study advanced from a rich literature provides robust facial feature detection under certain variations in lighting conditions and backgrounds.
In this paper, we propose a genetic algorithm based design procedure for a radial-basis function neural network. A Hierarchical Rank Density Genetic Algorithm (HRDGA) is used to evolve the neural network's topolog...
详细信息
In this paper, we propose a genetic algorithm based design procedure for a radial-basis function neural network. A Hierarchical Rank Density Genetic Algorithm (HRDGA) is used to evolve the neural network's topology and parameters simultaneously. Compared with traditional genetic algorithm based designs for neural networks, the hierarchical approach addresses several deficiencies highlighted in literature. In addition, the rank-density based fitness assignment technique is used to optimize the performance and topology of the evolved neural network to deal with the confliction between the training performance and network complexity. Instead of producing a single optimal solution, HRDGA provides a set of near-optimal neural networks to the designers so that they can have more flexibility for the final decision-making based on certain preferences. In terms of searching for a near-complete set of candidate networks with high performances, the networks designed by the proposed algorithm prove to be competitive, or even superior, to three other traditional radial-basis function networks for predicting Mackey–Glass chaotic time series.
The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dime...
详细信息
The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dimensional SOM structure with a growing self-organizing map. In the learning phase, a growing SOM is trained and the growing cell structure is used as the baseline framework. After the learning phase, the new projection method is used to map the input vector so that the input data is mapped to the structure of the SOM without having to plot the weight values, resulting in easy visualization of the data. The projection method is demonstrated on two data sets with promising results and a significantly reduced network size.
暂无评论