The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well-represented using ensemble of intelligent paradigms. To demonstrate the proposed technique, we considered Nasdaq-100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index. The intelligent paradigms consi...

In this paper, we propose a new tool based on Observed Time Difference of Arrival (OTDOA) technique in order to estimate both the position of the different User Equipments (UEs) and the Relative Time Differences (RTDs) between Node Bs in real UMTS networks from measurements reports providing the TM parameter and the locations of the sites. This technique results in a non-linear least squares es...

The use of cubic splines, instead of polynomials, in representing static nonlinearities in block structured models is considered. A system identification algorithm for the Hammerstein structure, a static nonlinearity followed by a linear filter, is developed in which the static nonlinearity is represented by a cubic spline. The identification algorithm, based on a separable least squares Levenb...

This paper investigates the ability of variously designed & trained Artificial Neural Network (ANN) to predict the probability of occurrence of Hypertension (HT) in a mixed (healthy + hypertensive, both sexes) patient population. To do this a multi layer feed-forward neural network with 13 inputs and 1 output was created with multiple hidden layers. Network parameters such as count of hidden la...

This paper addresses the problem of pattern classification using neural networks. Applying neural network classifiers for classifying a large volume of high dimensional data is a difficult task as the training process is computationally expensive. A parallel implementation of the known training paradigms offers a feasible solution to the problem. By exploiting the massively parallel structure o...

The kinetics of palm oil catalytic cracking over aluminum containing mesoporous silica Al-MCM-41 (5% Al) was investigated in a batch autoclave reactor at the temperatures range of 573 – 673 K. The catalyst was prepared by using sol-gel technique and has been characterized by nitrogen adsorption and x-ray diffraction methods. Surface area of 1276 m/g with average pore diameter of 2.54 nm and por...

2 Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran [email protected] Abstract: This paper proposes an adaptive Nonlinear Model Predictive Controller (NMPC) for hybrid position/velocity control of robot manipulators. Robot dynamics have generally uncertainties, including parameters variations, unknown nonlinearities of the robot, payload var...

Industrial robots are increasingly used in various applications where the robot accuracy becomes very important, hence calibrations of the robot’s kinematic parameters and the measurement system’s extrinsic parameters are required. However, the existing calibration approaches are either too cumbersome or require another expensive external measurement system such as laser tracker or measurement ...

We analyze the global convergence properties of some variants of regularized continuous Newton methods for convex optimization and monotone inclusions in Hilbert spaces. The regularization term is of LevenbergMarquardt type and acts in an open-loop or closed-loop form. In the open-loop case the regularization term may be of bounded variation.

The least squares adjustment (LSA) method is studied as an optimisation problem and shown to be equivalent to the undamped Gauss-Newton (GN) optimisation method. Three problem-independent damping modifications of the GN method are presented: the line-search method of Armijo (GNA); the LevenbergMarquardt algorithm (LM); and Levenberg-Marquardt with Powell dogleg (LMP). Furthermore, an additional...