Clutter usually has negative influence on the detection performance of radars. So, the recognition of clutters is crucial to detect targets and the role of clutters in detection cannot be ignored. The design of radar detectors and clutter classifiers are really complicated issues. Therefore, in this paper aims to classify radar clutters. The novel proposed MLP-based classifier for separating radar clutters is introduced. This classifier is designed with different hidden layers and five training algorithms. These training algorithms consist of Levenberg-Marquardt, conjugate gradient, resilient back-propagation, BFGS and one step secant algorithms. Statistical distributions are established models which widely used in the performance calculations of radar clutters. Hence In this research, Rayleigh, Log normal, Weibull and K-distribution clutters are utilized as input data. Then Burg’s reflection coefficients, skewness and kurtosis are three features which applied to extract the best characteristics of input data. In the next step, the proposed classifier is tested in different conditions and the results represent that the proposed MLP-based classifier is very successful and can distinguish clutters with high accuracy. Comparing the results of proposed technique and RBF-based classifier show that proposed method is more efficient. The results of simulations prove that the validity of MLP-based method.

Networks are useful tools for presenting the relationships between financial institutions. During the previous years, many scholars have found that using single-layer networks cannot properly characterize and explain complex systems. The purpose of this research is to introduce a multiplex network in order to analyze, as accurately as possible, all aspects of communication between banks in capital market of Iran. In this article, each bank represents a node and three layers of return, trading volume and market Cap have been presented for analyzing the idea of multiplex networks. We have used the Granger causality method to determine the direction between nodes. For understanding the topology structure of these layers, different concepts have been used. The research findings show that the value layer topology has a significant similarity with the trading volume layer. Also according to the measure of centrality it can be seen that the centrality varies in different layers.

In this article, three types of green's functions are presented for a narrow strip line (not a thin wire) inside or on a homogeneous dielectric, supposing quasi-TEM dominant mode. These functions have no singularity in contrast to so far presented ones, so that they can be used easily to determine the capacitance matrix of multi-layer and singlelayer homogeneous coupled microstrip lines. To obtain the green’s functions, the Laplace’s equation is solved analytically in Fourier integral or Fourier series expressions, taking into account the boundary conditions including the narrow strip. The validity and accuracy of three presented green’s functions are verified by some examples.

This paper concerns with a mathematical model considering customer satisfaction requirements in a supply chain. The model tradeoffs the supply chain ability to fulfill the customers’ requirements and the limited budget in a variety of production phases. The decisions made here help to determine the profit provider price and economic quantity while the effective supplier and priori requirements are found. A numerical example illustrates the applicability of the proposed mathematical model.