Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Multipole mixing ratios for gamma transition populated in from reaction have been studied by least square fitting method also transition strength ] for pure gamma transitions have been calculated taking into account the mean life time for these levels .

The method of operational matrices based on different types of polynomials such as Bernstein, shifted Legendre and Bernoulli polynomials will be presented and implemented to solve the nonlinear Blasius equations approximately. The nonlinear differential equation will be converted into a system of nonlinear algebraic equations that can be solved using Mathematica®12. The efficiency of these methods has been studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as the polynomial degree (n) increases, since the errors decrease. Moreover, the approximate solutions obtained by the proposed methods are compared with the solution of the 4th order Runge-Kutta method (RK4), which gives very

The Foreign Account Tax Compliance Act (FATCA) basically targets US citizens’ accounts hold at foreign banks and financial institutions blush, seems and non-financial sector by the Act:( retirement plan companies, investment funds, hedge funds and family investment companies.)

The non Compliance of Foreign of financial institutions act will lead to financial looses and harm regarding reputation, especially for the countries that rely on foreign relations in their financial and banking activities, in addition to deducting 30 % of their total incomes and sales coming from the USA. These institutions can avoid it by entering into agreement with the Internal Revenue Service's to be foreign financial institutions complied with the a

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

The effects of gamma irradiation on the structure of ZnS films , which preparing by flash evaporation method, are studied using XRD. Two peaks of (111), (220) orientations are appeared in X ray chart indicating the cubic phase of the films .The lattice parameter, grain size, average internal stress, microstrain, dislocation density and degree of preferred orientation in the film are calculated and correlated with gamma irradiation.

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

The study sought to identify the attitudes of PhD students towards establishing the field of educational administration. The study followed the descriptive survey method. The questionnaire was used to collect information from the study community consisting of (95) male and female students in the department of educational administration and Planning. Among the most important results about students ’attitudes towards establishing the educational administration field are the following: 1) identifying the necessity of establishing the educational administration field. 2) Encouraging students to attend seminars and scientific conferences in Islamic rooting. 3) there are no statistically significant differences in the attitudes of doctoral s