Aiming at the time-consuming problem of full-wave (FW) simulation scattering characteristics traditional graphene reconfigurable reflectarray antenna, a fast prediction method electromagnetic (EM) response based on deep learning is proposed. The convolutional neural network (CNN) in effectively used research this paper. This first discretizes input vector (patch geometry, chemical potential, fr...

In this paper, we present a new method to enhance classification performance of a multiple classifier system by combining a boosting technique called AdaBoost.M2 and Kernel Discriminant Analysis (KDA). To reduce the dependency between classifier outputs and to speed up the learning, each classifier is trained in a different feature space, which is obtained by applying KDA to a small set of hard...

This paper presents mesh-free procedures for solving linear differential equations (ODEs and elliptic PDEs) based on multiquadric (MQ) radial basis function networks (RBFNs). Based on our study of approximation of function and its derivatives using RBFNs that was reported in an earlier paper (Mai-Duy, N. & Tran-Cong, T. (1999). Approximation of function and its derivatives using radial basis fu...

Agriculture is suffering from the problem of low fertility and climate hazards such as increased pest attacks diseases. Early prediction can be very helpful in improving productivity agriculture. Insect (whitefly) attack has a high influence on cotton crop yield. Internet Things solution proposed to predict whitefly take prevention measures. An insect system (IPPS) was developed with help RBFN ...

In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well...

NODElib is an open source programming library that can be used to rapidly develop complex neural network simulations. In NODElib, all neural architectures are considered special cases of a general feedforward model; thus, advance numerical routines (such as calculating the Hessian, optimizing the Jacobian, performing quasi-Newton, conjugate gradient, backprop, or Leverberg-Marqardt, etc.) are a...

In recent years, the future trend of micro HDD driver IC for large capacity micro HDD is to become lighter, thinner, shorter and smaller. Among all the options available for micro HDD driver IC’s assembly, warpage is an important issue related to micro HDD driver IC manufacturability and reliability. The optimal packaging manufacturing process for driver IC for micro HDD is chip scale package (...

In this paper, we present a comparative study of different neural network models for forecasting the weather of Vancouver, British Columbia, Canada. For developing the models, we used one year’s data comprising of daily maximum and minimum temperature and wind-speed. We used a Multi-Layered Perceptron (MLP) and an Elman Recurrent Neural Network (ERNN) trained using the one-step-secant and Leven...

Abstract—This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homoge...