In standard wavelet methods, the empirical wavelet coefficients are thresholded term by term, on the basis of their individual magnitudes. Information on other coefficients has no influence on the treatment of particular coefficients. We propose and investigate a wavelet shrinkage method that incorporates information on neighboring coefficients into the decision making. The coefficients are con...

The efficiency of distribution systems is largely affected by the performances of distribution centres. The main objective of this paper is to develop and propose a DEA model for distribution centres efficiency measuring that can help managers in decision making and improving the efficiency. Due to numerous indicators that describe DCs operating, the main problem is indicators selection. In ord...

Abstract In this paper, we propose a bounded DEA based model to measure the overall risk of failure modes. In the proposed model risk is measured within the range of an interval, whose performance is definitely superior to any one. The risks, obtained from bounded DEA models, turn out to be all intervals and are referred to as interval risk, which combine the best and the worst relative risk in...

The purpose and goal of this assignment was to design and implement a small system to predict a class of a single numerical variable in a binomial class problem. In order to do this, it was requested to implement or to think of one or more “1D classifiers”, discussing their computational complexities in the learning phases, the performances on the given dataset, the differences and similarities...

In this paper, normal cloud model and evidential reasoning (E-R) approach is used in multiple attribute decision analysis (MADA) problems. Different attributes Belief function are represented by cloud model interval. Using cloud model generating algorithm, belief degree interval is obtained without numerical computation. In addition, it is reasonable and it accords with human’s mind. Evidential...

In this paper a Matlab-based toolbox for the input-output system inversion of linear systems is presented. Different methods, based either on analytical or numerical approaches, are implemented. The toolbox can be exploited in the design of a feedforward action for control systems in different contexts in order to improve performances in the set-point regulation. The use of a pre-actuation and ...

The effect of changes in operating conditions due to fault occurrences can alter performances in industrial processes. One way of preventing performances from degradation is to modify the control law in order to maintain the functioning of the process under acceptable operating conditions. In this paper, a Fault Tolerant Control of an Activated Sludge Process is presented. Free fault data are r...

This paper deals with theoretical and practical results on aperture synthesis. Full attention is devoted to the Fourier synthesis operation, which proves to be the central issue with regard to the global problem. Different regularization techniques are shown to derive from a unique principle: the Principle of Maximum Entropy on the Mean (PMEM). This is the case for WIPE, as well as for the trad...

We propose a new method of discriminant analysis, called High Dimensional Discriminant Analysis (HHDA). Our approach is based on the assumption that high dimensional data live in different subspaces with low dimensionality. Thus, HDDA reduces the dimension for each class independently and regularizes class conditional covariance matrices in order to adapt the Gaussian framework to high dimensio...

In this paper, a compact tri-band impedance transformer by utilizing stubbed coupling line for matching a load at three arbitrary frequencies is proposed. The transformer is composed of two parts, and each part is constructed from parallel-coupled transmission lines. Two structures with different configurations of the proposed transformer have been given and analyzed. Then, the close-form equat...