Janusz A. Starzyk

A self-organizing learning array system for power quality classification based on wavelet transform

This paper proposed a novel approach for the Power Quality (PQ) disturbances classification based on the wavelet transform and self organizing learning array (SOLAR) system. Wavelet transform is utilized to extract feature vectors for various PQ disturbances based on the multiresolution analysis (MRA). These feature vectors then are applied to a SOLAR system for training and testing. SOLAR has three advantageous over a typical neural network: data driven learning, local interconnections and entropy based self-organization. Several typical PQ disturbances are taken into consideration in this paper. Comparison research between the proposed method, the support vector machine (SVM) method and existing literature reports show that the proposed method can provide accurate classification results. By the hypothesis test of the averages, it is shown that there is no statistically significant difference in performance of the proposed method for PQ classification when different wavelets are chosen. This means one can choose the wavelet with short wavelet filter length to achieve good classification results as well as small computational cost. Gaussian white noise is considered and the Monte Carlo method is used to simulate the performance of the proposed method in different noise conditions.

A DC-DC charge pump design based on voltage doublers

A novel organization of switched capacitor charge pump circuits based on voltage doubler structures is presented in this paper. Each voltage doubler takes a dc input and outputs a doubled dc voltage. By cascading n voltage doublers the output voltage increases up to 2/sup n/ times. A two-phase voltage doubler and a multiphase voltage doubler (MPVD) structures are discussed and design considerations are presented. A simulator working in the Q-V realm was used for simplified circuit level simulation. In order to evaluate the power delivered by a charge pump, a resistive load is attached to the output of the charge pump and an equivalent capacitance is evaluated. A comparison of the voltage doubler circuits with Dickson charge pump and Makowskis voltage multiplier is presented in terms of the area requirements, the voltage gain, and the power level. This paper also identifies optimum loading conditions for different configurations of the charge pumps. Design guidelines for the desired voltage and power levels are discussed. A two-stage MPVD was fabricated using MOSIS 2.0-/spl mu/m CMOS technology. It was designed with internal frequency regulation to reduce power consumption under no load condition.

Robust Exponential Stability of Uncertain Delayed Neural Networks With Stochastic Perturbation and Impulse Effects

This paper focuses on the hybrid effects of parameter uncertainty, stochastic perturbation, and impulses on global stability of delayed neural networks. By using the Ito formula, Lyapunov function, and Halanay inequality, we established several mean-square stability criteria from which we can estimate the feasible bounds of impulses, provided that parameter uncertainty and stochastic perturbations are well-constrained. Moreover, the present method can also be applied to general differential systems with stochastic perturbation and impulses.

Flowgraph analysis of large electronic networks

The paper presents a new method for signal flowgraph analysis of large electronic networks. A hierarchical decomposition approach is realized using the so-called upward analysis of the decomposed network. This approach allows fully symbolic network formulas to be obtained in time linearly proportional to the size of the network. A multiconnection characterization, suitable for upward analysis, has been defined and used in topological formulas. Examples of large scale networks analysis are discussed. The approach can be used to obtain symbolic solutions of linear systems of equations.

Entropy-based optimum test points selection for analog fault dictionary techniques

An efficient method to select an optimum set of test points for dictionary techniques in analog fault diagnosis is proposed. This is done by searching for the minimum of the entropy index based on the available test points. First, the two-dimensional integer-coded dictionary is constructed whose entries are measurements associated with faults and test points. The problem of optimum test points selection is, thus, transformed to the selection of the columns that isolate the rows of the dictionary. Then, the likelihood for a column to be chosen based on the size of its ambiguity set is evaluated using the minimum entropy index of test points. Finally, the test point with the minimum entropy index is selected to construct the optimum set of test points. The proposed entropy-based method to select a local minimum set of test points is polynomial bounded in computational cost. The comparison between the proposed method and other reported test points selection methods is carried out by statistical experiments. The results indicate that the proposed method more efficiently and more accurately finds the locally optimum set of test points and is practical for large scale analog systems.

Fast Vanishing-Point Detection in Unstructured Environments

Vision-based road detection in unstructured environments is a challenging problem as there are hardly any discernible and invariant features that can characterize the road or its boundaries in such environments. However, a salient and consistent feature of most roads or tracks regardless of type of the environments is that their edges, boundaries, and even ruts and tire tracks left by previous vehicles on the path appear to converge into a single point known as the vanishing point. Hence, estimating this vanishing point plays a pivotal role in the determination of the direction of the road. In this paper, we propose a novel methodology based on image texture analysis for the fast estimation of the vanishing point in challenging and unstructured roads. The key attributes of the methodology consist of the optimal local dominant orientation method that uses joint activities of only four Gabor filters to precisely estimate the local dominant orientation at each pixel location in the image plane, the weighting of each pixel based on its dominant orientation, and an adaptive distance-based voting scheme for the estimation of the vanishing point. A series of quantitative and qualitative analyses are presented using natural data sets from the Defense Advanced Research Projects Agency Grand Challenge projects to demonstrate the effectiveness and the accuracy of the proposed methodology.

Architecture and application of a dynamically reconfigurable hardware array for future mobile communication systems

The evolving of current and future broadband access techniques into the wireless domain introduces new and flexible network architectures with difficult and interesting challenges. The system designers are faced with a challenging set of problems that stem from access mechanisms, energy conservation, error rate, transmission speed characteristics of the wireless links and mobility aspects. This paper presents first the major challenges in realizing flexible microelectronic system solutions for future mobile communication applications. Based thereupon, the architecture design of flexible system-on-a-chip solutions in the digital baseband processing for future mobile radio devices is discussed. The focus of the paper is the introduction of a new parallel and dynamically reconfigurable hardware architecture tailored to this application area. Its performance issues and potential are discussed by the implementation of a flexible and computation-intensive component of future mobile terminals.

A unified decomposition approach for fault location in large analog circuits

This paper deals with the problem of fault location in analog circuits. The circuit under test is decomposed into subnetworks using nodes at which voltages have been measured. We localize the faults to within the smallest possible subnetworks according to the final decomposition. Then, further identification of the faulty elements inside the subnetworks is carried out. The method is applicable to large-networks, linear or nonlinear. It requires a limited-number of measurement nodes and its on-line computation requirements are minimal. The method is based on checking the consistency of KCL in the decomposed circuit. A measure of the effect of tolerances on the elements is introduced, and a number of examples are considered to illustrate the application of the method in both the linear and the nonlinear cases.

A Mathematical Foundation for Improved Reduct Generation in Information Systems

Abstract. When data sets are analyzed, statistical pattern recognition is often used to find the information hidden in the data. Another approach to information discovery is data mining. Data mining is concerned with finding previously undiscovered relationships in data sets. Rough set theory provides a theoretical basis from which to find these undiscovered relationships. We define a new theoretical concept, strong compressibility, and present the mathematical foundation for an efficient algorithm, the Expansion Algorithm, for generation of all reducts of an information system. The process of finding reducts has been proven to be NP-hard. Using the elimination method, problems of size 13 could be solved in reasonable times. Using our Expansion Algorithm, the size of problems that can be solved has grown to 40. Further, by using the strong compressibility property in the Expansion Algorithm, additional savings of up to 50% can be achieved. This paper presents this algorithm and the simulation results obtained from randomly generated information systems.

Determination of an optimum set of testable components in the fault diagnosis of analog linear circuits

A procedure for the determination of an optimum set of testable components in the fault diagnosis of analog linear circuits is presented. The proposed method has its theoretical foundation in the testability concept and in the canonical ambiguity group concept. New considerations relevant to the existence of unique solution in the k-fault diagnosis problem of analog linear circuits are presented, and examples of application of the developed procedure are considered by exploiting a software package based on symbolic analysis techniques.