By combing the theories of the switched systems and the interval neural networks, the mathematics model of the switched interval neural networks with discrete and distributed timevarying delays of neural type is presented. A set of the interval parameter uncertainty neural networks with discrete and distributed time-varying delays of neural type are used as the individual subsystem, and an arbi...

in the present paper, we introduce the sequence space [{l_p}(e,delta) = left{ x = (x_n)_{n = 1}^infty : sum_{n = 1}^infty left|  sum_{j in {e_n}} x_j - sum_{j in e_{n + 1}} x_jright| ^p < infty right},] where $e=(e_n)$ is a partition of finite subsets of the positive integers and $pge 1$. we investigate its topological properties and inclusion relations. moreover, we consider the problem of fin...

Infimum-supremum interval arithmetic is widely used because of ease of implementation and narrow results. In this note we show that the overestimation of midpoint-radius interval arithmetic compared to power set operations is uniformly bounded by a factor 1.5 in radius. This is true for the four basic operations as well as for vector and matrix operations, over real and over complex numbers. Mo...

We consider linear systems of algebraic equations Su = f with tridiagonal interval matrix S and interval vector f An interval version of the sweep method allows us to find an interval vector u = ( u t , u 2 , . . . , u n ) T that contains the united set of solutions of the system. In the paper we present estimates of the absolute value and the width of the intervals ui, i = 1, 2 , . . . , ~z ti...

Analytic hierarchy process (AHP) is a useful method in multi-criteria decision making problems. Crisp comparison matrices produce crisp weight estimates. It is logical for an interval or fuzzy comparison matrix to give an interval or fuzzy weight estimate. In this paper, a new method is proposed to generate interval weight estimate from an interval comparison matrix, which can be either consist...

This paper deals with the problem of finding, for a given graph and a given natural number k, a subgraph of k nodes with a maximum number of edges. This problem is known as the k-cluster problem and it is NP-hard on general graphs as well as on chordal graphs. In this paper, it is shown that the k-cluster problem is solvable in polynomial time on interval graphs. In particular, we present two p...

Multiple classifiers combination is a technique that combines the decisions of different classifiers as to reduce the variance of estimation errors and improve the overall classification accuracy. A new multiple classifiers fusion method integrated classifier selection and classifier combination is proposed in this paper. It is base on interval-valued fuzzy permutation. Firstly, normalize all c...

This paper deals with the problem of finding, for a given graph and a given natural number k, a subgraph of k nodes with a maximum number of edges. This problem is known as the k-cluster problem and it is NP-hard on general graphs as well as on chordal graphs. In this paper, it is shown that the k-cluster problem is solvable in polynomial time on interval graphs. In particular, we present two p...

Many machine learning and data-related applications require the knowledge of approximate ranks of large data matrices at hand. This letter presents two computationally inexpensive techniques to estimate the approximate ranks of such matrices. These techniques exploit approximate spectral densities, popular in physics, which are probability density distributions that measure the likelihood of fi...

A graph is said to be $I$-eigenvalue free if it has no eigenvalues in the interval $I$ with respect adjacency matrix $A$. In this paper we present twoalgorithms for generating threshold graphs.