MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Considers the problems of robust stability and stabilization for uncertain continuous singular systems with state delay. The parametric uncertainty is assumed to be norm bounded. The purpose of the robust stability problem is to give conditions such that the uncertain singular system is regular, impulse free, and stable for all admissible uncertainties, while the purpose of the robust stabilization is to design a state feedback control law such that the resulting closed-loop system is robustly stable. These problems are solved via the notions of generalized quadratic stability and generalized quadratic stabilization, respectively. Necessary and sufficient conditions for generalized quadratic stability and generalized quadratic stabilization are derived. A strict linear matrix inequality (LMI) design approach is developed. An explicit expression for the desired robust state feedback control law is also given. Finally, a numerical example is provided to demonstrate the application of the proposed method.

/pdf/robust-stability-and-stabilization-for-singular-systems-with-4zvzx7fnc7.pdf

Robust stability and stabilization for singular systems with state delay and parameter uncertainty

Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya's theorem

This paper presents the stability analysis of interval type-2 fuzzy-model-based (FMB) control systems. To investigate the system stability, an interval type-2 Takagi-Sugeno (T-S) fuzzy model, which can be regarded as a collection of a number of type-1 T-S fuzzy models, is proposed to represent the nonlinear plant subject to parameter uncertainties. With the lower and upper membership functions, the parameter uncertainties can be effectively captured. Based on the interval type-2 T-S fuzzy model, an interval type-2 fuzzy controller is proposed to close the feedback loop. To facilitate the stability analysis, the information of the footprint of uncertainty is used to develop some membership function conditions, which allow the introduction of slack matrices to handle the parameter uncertainties in the stability analysis. Stability conditions in terms of linear matrix inequalities are derived using a Lyapunov-based approach. Simulation examples are given to illustrate the effectiveness of the proposed interval type-2 FMB control approach.

Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems

This paper investigates the problem of output feedback robust $\mathscr{H}_{\infty }$ control for a class of nonlinear spatially distributed systems described by first-order hyperbolic partial differential equations (PDEs) with Markovian jumping actuator faults. The nonlinear hyperbolic PDE systems are first expressed by Takagi–Sugeno fuzzy models with parameter uncertainties, and then, the objective is to design a reliable distributed fuzzy static output feedback controller guaranteeing the stochastic exponential stability of the resulting closed-loop system with certain $\mathscr{H}_{\infty }$ disturbance attenuation performance. Based on a Markovian Lyapunov functional combined with some matrix inequality convexification techniques, two approaches are developed for reliable fuzzy static output feedback controller design of the underlying fuzzy PDE systems. It is shown that the controller gains can be obtained by solving a set of finite linear matrix inequalities based on the finite-difference method in space. Finally, two examples are presented to demonstrate the effectiveness of the proposed methods.

Fuzzy-Model-Based Reliable Static Output Feedback $\mathscr{H}_{\infty }$ Control of Nonlinear Hyperbolic PDE Systems

The robust stability of linear continuous-time generalized state-space systems with structured perturbations is investigated in this paper. Based on the maximum modulus principle and spectral radius of matrices, a new upper bound of perturbations is obtained to ensure that the perturbed generalized state-space system remains regular, impulse-free, and asymptotically stable. It is shown that this bound is less conservative than the existing one. Furthermore, the computation required in the proposed approach is also simpler.

An improved bound for stability robustness of uncertain generalized state-space systems

An experimental design utilizing artificial neural networks (ANNs), the Taguchi method, and the genetic algorithm (GA) is proposed to obtain optimal processing parameters for cathode arc plasma deposition of ZnO thin films on a glass substrate. The Taguchi method’s orthogonal array is used to minimize the number of required experiments and to gather the experimental data. An ANN is then used to construct a system model based on the experimental data. Finally, the GA is used to determine the optimal process parameters. The average resistivity obtained from the optimal processing parameters is $3.19 \times 10^{-3} ~\Omega $ -cm and the average transmittance obtained is 86.04%, both of which improve on results obtained using the Taguchi method alone ( $3.69 \times 10^{-3}\Omega $ -cm and 85.41%). This indicates that the proposed design is a viable approach for determining the optimal process parameters.

An Experimental Design for Processing Parameter Optimization for Cathode Arc Plasma Deposition of ZnO Films

To provide more clinically convenient image fusions for adaptive radiotherapy (ART), an automatic rigid and deformable image registration framework (AIRF) is developed for multimodal visualization of multiple chronological images and multiple radiotherapy (RT) plans Our hybrid image registration framework, AIRF, uses a faster but less accurate rigid registration method to provide an initial registration, followed by a slower but more accurate deformable registration method to fine tune the final registration A multi-resolution approach is also employed in the image registration process to further improve the registration accuracy, robustness and efficiency Volume visualization is provided to guide the automatic image registration process because it can reduce the global positioning error that results from a partial 3D visual presentation in the three conventional orthogonal planar views (axial, sagittal, and coronal) The AIRF can automatically align multiple volumetric images of patients taken over an extended period of time and can merge multiple radiotherapy plans based on different planning computed tomography (CT) images It offers illustrative 3D volumetric visualization, hybrid rigid and deformable image registration, and automatic transfer of RT dose distribution and RT structure models such as treatment targets and organs at risk (OARs) onto chronological images The AIRF can automatically register multiple volumetric image datasets of patients taken over an extended period of time and can merge multiple RT plans based on different planning CT images for 4D or adaptive radiotherapy

3D Volumetric Visualization with Automatic Rigid and Deformable Hybrid Image Registration for Adaptive Radiotherapy

This paper investigates the problem of H/spl infin/ control for T-S fuzzy discrete-time descriptor systems. Firstly, an analysis result for H/spl infin/ control is derived and characterized by a set of linear matrix inequalities (LMIs). The derived analysis condition is then applied to design an H/spl infin/ fuzzy controller. In T-S fuzzy discrete-time descriptor systems, due to singularity of E-matrix, Schur complement cannot be applied to solve the nonlinear Lyapunov inequality anymore for H control. The difficulty is overcome by the approach proposed in this paper. Before this presentation, no result about the H/spl infin/ control of T-S fuzzy discrete-time descriptor systems is available in the literature, the paper seems the first one to tackle it from the theoretical aspect.

H/spl infin/ Control for Discrete-Time Fuzzy Descriptor Systems

The robustness of uncertain generalized state-space systems is investigated in this paper. By transforming the robustness problem to a rank problem, we provide a simple method to find the exact unidirectional perturbation bounds under which the stability, regularity, and impulse immunity are simultaneously preserved. The bound can be obtained in a closed form. The familiar result developed by Fu-Barmish (1988) becomes a special case of ours.

Chun-Hsiung Fang

Papers

An improved bound for stability robustness of uncertain generalized state-space systems

An Experimental Design for Processing Parameter Optimization for Cathode Arc Plasma Deposition of ZnO Films

3D Volumetric Visualization with Automatic Rigid and Deformable Hybrid Image Registration for Adaptive Radiotherapy

H/spl infin/ Control for Discrete-Time Fuzzy Descriptor Systems

Exact unidirectional perturbation bounds for robust stability of uncertain generalized state-space systems