Kernel-based feature extraction is widely used in image classification, and different kernel methods extract the features based different criterion. KPCA maximizes the determinant of the total scatter matrix of the transformed sample, while KDA seeks the direction of discrimination. KPCA preserves the global property, and KDA utilizes class information to enhance its discriminative ability so a...

in this paper, a method for establishing a support criterion or poverty line is developed based on engel’s law and domestic nutritional values. the support criterion is differentiated across rural and urban areas. an important result is that for 1989, people who spend less than 108,000 rials annually lie inside the poverty line in urban areas. a further important result is that food should be g...

In this paper, a new approach on image registration is presented. We introduce a novel conceptionnormal vector information (NVI) to evaluate the similarity between two images. NVI method takes advantage of the relationship between voxels in the image to extract the normal vector (NV) information of each voxel. Firstly, NVI criterion is presented. Then, based on the criterion, we find that NVI r...

In this paper, we have considered a series-parallel system to find out optimum system reliability with an additional entropy objective function. Maximum system reliability of series-parallel system is depending on proper allocation of redundancy component in different stage. The goal of entropy based reliability redundancy allocation problem is to find optimal number of redundancy component in ...

In this paper, a new technique has been designed to capture the outline of 2D shapes using cubic B´ezier curves. The proposed technique avoids the traditional method of optimizing the global squared fitting error and emphasizes the local control of data points. A maximum error has been determined to preserve the absolute fitting error less than a criterion and it administers the process of curv...

Memristive neural networks are a novel topic in the design and construction of brain-like circuitry system. This paper addresses a challenging problem: How to derive some less conservative theoretical results on the stability and attractability for memristive neural networks? In this paper, a new comparison method and segmentation method of state space are developed. A succinct criterion is pro...

In this paper, we introduce and analyze a simple adaptive finite element method for second order elliptic partial differential equations. The marking strategy depends on whether the data oscillation is sufficiently small compared to the error estimator in the current mesh. If the oscillation is small compared to the error estimator, we mark as many edges such that their contributions to the loc...

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Baye...

We propose an online adaptive local-global POD-DEIM model reduction method for flows in heterogeneous porous media. The main idea of the proposed method is to use local online indicators to decide on the global update, which is performed via reduced cost local multiscale basis functions. This unique local-global online combination allows (1) developing local indicators that are used for both lo...

augmented downhill simplex method (adsm) is introduced here, that is a heuristic combination of downhill simplex method (dsm) with random search algorithm. in fact, dsm is an interpretable nonlinear local optimization method. however, it is a local exploitation algorithm; so, it can be trapped in a local minimum. in contrast, random search is a global exploration, but less efficient. here, rand...