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

Sufficient conditions are proposed to guarantee robust pole location inside some specified regions for linear uncertain implicit systems. The robust control problems of uncertain implicit systems are more complicated than those of state-space systems since not only robustness of stability but regularity and freedom of impulse as well should be considered simultaneously. The explicit bounds on linear time-invariant perturbations with highly structured information can be obtained by using the techniques of spectral radius and nonnegative matrices. >

Robustness of regional pole placement for uncertain continuous-time implicit systems

Effect of the Ti-target arc current on the properties of Ti-doped ZnO thin films prepared by dual-target cathodic arc plasma deposition

A simple approach is presented to investigate the robustness of pole-clustering in specified regions for generalized state-space systems with structured uncertainties. The proposed method is computationally simple and the obtained results are less conservative than the existing ones. Furthermore, the present approach can deal with more types of regions than other approaches shown in the literature. >

Regional pole-clustering robustness for uncertain generalized state-space systems

The Quantitative Coronary Analysis (QCA) is a useful method for physicians to diagnose heart artery stenosis. So the precision of coronary angiography image quality is very definite important. In this study we present a precision 2-D image processing method that combines gradient segmentation and region segmentation approaches with an entropy maximization procedure. This method allows us to utilize all available information to achieve the most robust segmentation results for coronary angiography analysis. The aim is to improve the methods of 2-D coronary angiography image processing those usually lack such as precision. The example of coronary angiography data of true medical images were used to test the validity of our method. We found that our method not only achieved the precision we sought but also has many interesting applications that shall be most useful in medical practices.

Quantitative Coronary Analysis Medical Image Processing Improved by Combining Wavelet Edge Detection and Segmentation

A less conservative condition for robust D-stability of linear systems with polytopic uncertainties is proposed. The robust D-stability can be easily attested by means of a feasibility test of a set of linear matrix inequalities (LMIs) involving only the vertices of the polytope. It is shown that the proposed condition include a lot of conditions published recently as particular cases. To the best of authors' knowledge, the present result is the least conservative in comparison with other conditions currently available in the field of robust D-stability analysis for polytopic uncertain systems

Chun-Hsiung Fang

Papers

Robustness of regional pole placement for uncertain continuous-time implicit systems

Effect of the Ti-target arc current on the properties of Ti-doped ZnO thin films prepared by dual-target cathodic arc plasma deposition

Regional pole-clustering robustness for uncertain generalized state-space systems

Quantitative Coronary Analysis Medical Image Processing Improved by Combining Wavelet Edge Detection and Segmentation

An improved LMI-based D-stability condition for polytopic uncertain systems