Abstract A new method to enclose the pseudospectrum via numerical range of inverse a matrix or linear operator is presented. The applied finite-dimensional discretizations an on infinite-dimensional Hilbert space, and convergence results for different approximation schemes are obtained, including finite element methods. We show that full contained in intersection sets which expressed terms rang...

during the last decades a new class of materials named fiber/metal laminates (fmls) was introduced. it is a hybrid composite consisting of alternating thin layers of metal sheets and fiber-reinforced composite material. fmls have both low weight and good mechanical properties. in this study, the impact behavior of this attractive material is investigated. the effect of fiber angle, stacking seq...

‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎Then‎, ‎we use...

Compressive imaging using sparsity constraints is a very promising field of microscopy that provides dramatic enhancement the spatial resolution beyond Abbe diffraction limit. Moreover, it simultaneously overcomes Nyquist limit by reconstructing an N -pixel image from less than single-point measurements. Here we present fundamental limits noiseless compressive via constraints, speckle illuminat...

We present a new discretization method based on Area under ROC Curve (AUC) measure. Maximum Area under ROC Curve Based Discretization (MAD) is a global, static and supervised discretization method. It discretizes a continuous feature in a way that the AUC based only on that feature is to be maximized. The proposed method is compared with alternative discretization methods such as Entropy-MDLP (...

In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling,...

We propose a new genetic fuzzy discretization method with feature selection for the pattern classification problems. Traditional discretization methods categorize a continuous attribute into a number of bins. Because they are made on crisp discretization, there exists considerable information loss. Fuzzy discretization allows overlapping intervals and reflects linguistic classification. However...