Biometrics is a proper way of identifying human beings based on certain physiological characteristics and behavioral characteristics. Some of the physiological characteristics are fingerprint, face, DNA and iris. Some of the useful behavioral traits are gait and voice. But ear biometrics has recently emerged as a new area in biometrics. A great possibility for use of human ears for identificati...

With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least square migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, vario...

This paper deals with the simultaneous states and parameters estimation of an ozonation reactor using a dynamic neural network and the least squares method. We use a dynamic model derived from mass balance considerations. We propose a continuous time algorithm which includes two parallel procedures: state estimation using a Dynamic Neural Network (DNN) and parameters identification based on Lea...

We present the theory and numerical results for least-squares migration of traces generated by simultaneous sources. Numerical tests show that standard seismic data processing, such as stacking and migration, can effectively suppress some crosstalk associated with simultaneous sources data, and so can separate shot gathers from one another. In contrast, LSM can remove most of the noise from sim...

in this paper, three dimensional (3d) static and dynamic analysis of thick plates based on the meshless local petrov-galerkin (mlpg) is presented. using the kinematics of a three-dimensional continuum, the local weak form of the equilibrium equations is derived. a weak formulation for the set of governing equations is transformed into local integral equations on local sub-domains by using a uni...

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The Least Mean Square (LMS) algorithm, introduced by Widrow and Hoff in 1959 [12] is an adaptive algorithm, which uses a gradient-based method of steepest decent [10]. LMS algorithm uses the estimates of the gradient vector from the available data. LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vect...