analysis of time series data can involve the inversion of large covariance matrices. for theclass of arma (p, q) processes there are no exact explicit expressions for these inverses, except for thema (1) process. in practice, the sample covariance matrix can be very large and inversion can becomputationally time consuming and so approximate explicit expressions for the inverse are desirable.thi...

the problem of discrimination between two stationary ar(p) plus noise processes is consideredwhen the noise process are different in two models. the discrimination rule leads to a quadratic form withcumbersome matrices. an approximate and analytic form is given to distribution of the discriminant. thesimulation study has been used to show the performance of discrimination rule. the cumulants of...

introduction: the aim of this study was to evaluate the effect of proximal contour of class ii composite restorations placed with straight or contoured matrix band using composite resins with different modulus of elasticity on stress distribution by finite element method. methods: in order to evaluate the stress distribution of class ii composite restorations using finite element method, upper ...

Introduction: The aim of this study was to evaluate the effect of proximal contour of class II composite restorations placed with straight or contoured matrix band using composite resins with different modulus of elasticity on stress distribution by finite element method. Methods: In order to evaluate the stress distribution of class II composite restorations using finite element method, upper ...

This paper presents a modified digital image watermarking method based on nonnegative matrix factorization. Firstly, host image is factorized to the product of three nonnegative matrices. Then, the centric matrix is transferred to discrete cosine transform domain. Watermark is embedded in low frequency band of this matrix and next, the reverse of the transform is computed. Finally, watermarked ...

This paper presents a modified digital image watermarking method based on nonnegative matrix factorization. Firstly, host image is factorized to the product of three nonnegative matrices. Then, the centric matrix is transferred to discrete cosine transform domain. Watermark is embedded in low frequency band of this matrix and next, the reverse of the transform is computed. Finally, watermarked ...