breast cancer is the second largest cause of cancer deaths among women. at the same time, it is also among the most curable cancer types if it can be diagnosed early. this paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. the proposed method includes three main modules: the feature extraction module, the classifier module and the optimization module. in t...

Supervisory control and fault diagnosis of hybrid systems need to have complete information about the discrete states transitions of the underling system. From this point of view, the hybrid system should be abstracted to a Discrete Trace Transition System (DTTS) and represented by a discrete mode transition graph. In this paper an effective method is proposed for generating discrete mode trans...

Introduction: All of the Imaging modalities have advantages and disadvantages alone. So if we want to have the best and perfect image, combining these modalities produces something we desired. PET-MR images consist of morphologic and metabolic data. MRI and PET provide high spatial and contrast resolution and high sensitivity and molecular information respectively. Hybrid PET-...

We outline an approach to modelling and reasoning about hybrid systems with the Event-B method supported by the Rodin toolset. The approach uses continuous functions over real intervals to model the evolution of continuous values over time. Nondeterministic interval events are used to specify how continuous variables evolve within an operating mode. Refinement is used to constrain the choice of...

A hybrid adaptive subtraction scheme is proposed. This hybrid scheme uses predictionerror filters as covariance operators within the filter-estimation step. This methods proves to be the most efficient when the noise and signal interfere. Although prediction-error filters are utilized, this technique is not a pattern-recognition technique: it simply tries to remove the correlated signal informa...

In this paper, a hybrid image denoising method that is based on locally adaptive window-based maximum likelihood (LAWML) and NeighShrink. The LAWML is doubly stochastic process models which denoise an image by exploiting the dependency of local wavelet coefficients within each scale. The LAWML needs a global optimal neighboring window. The NeighShrink thresholding scheme uses the immediate neig...

In this paper, we introduce hybrid of block-pulse functions and Bernstein polynomials and derive operational matrices of integration, dual, differentiation, product and delay of these hybrid functions by a general procedure that can be used for other polynomials or orthogonal functions. Then, we utilize them to solve delay differential equations and time-delay system. The method is based upon e...

In this work, a functional approximation method for calculating the linear functional of the solution of second-kind Fredholm integral equations is developed. When the method is applied to the collocation method or to the multi-projection method, it generates approximations which exhibit superconvergence. © 2008 Elsevier Ltd. All rights reserved.

Identifying individuals using biometric methods has recently gained growing interest from computer vision researchers for security purposes at places like airport, banks etc. Gait recognition aims essentially to address this problem by identifying people at a distance based on the way they walk i.e., by tracking a number of feature points or gait signatures. We describe a new model-based featur...

The discrete Fourier transform is one of the top ten algorithms of the 20-th century, frequently used in the analysis of signals. It is known to be very stable and of low computational complexity. When the bandwidth is large or the spectrum is sparse, sampling at the Shannon-Nyquist rate may however be prohibitive. We propose a new hybrid technique that exploits the spectral sparsity. Several s...