this study proposes a new linear approximation for solving the dynamic response equations of a rocking rigid block. linearization assumptions which have already been used by hounser and other researchers cannot be valid for all rocking blocks with various slenderness ratios and dimensions; hence, developing new methods which can result in better approximation of governing equations while keepin...

Function approximation is to find the underlying relationship from à given finite input-output data. It has numerous applications such as prediction, pattern recognition, data mining and classification etc. Multilayered feed-forward neural networks (MLFNNs) with the use of back propagation algorithm have been extensively used for the purpose of function approximation recently. Another class of ...

Abstract. Let W be an integrable positive Hermitian q × q-matrix valued function on the dual group of a discrete abelian group G such that W is integrable. Generalizing results of T. Nakazi and ofA. G. Miamee [N] andM. Pourahmadi [MiP] for q = 1 we establish a correspondencebetween trigonometric approximation problems in L(W ) and certain approximation problems in L(W). The result is applied to...

In this paper, we introduce and study a generalized Yosida approximation operator associated to H(·, ·)-co-accretive operator and discuss some of its properties. Using the concept of graph convergence and resolvent operator, we establish the convergence for generalized Yosida approximation operator. Also, we show an equivalence between graph convergence for H(·, ·)-co-accretive operator and gen...

in this article, the crystallization of polyethylene is investigated by the modified weighted density approximation. also, a direct correlation function of polyethylene based on the rism theory is used. the free energy of a polyethylene is calculated using the density functional theory. the crystallization and also the solid and liquid densities of polyethylene are calculated and compared with ...

This paper presents a filter approach for estimating the state of nonlinear dynamic systems based on recursive approximation of posterior densities by means of Dirac mixture functions. The filter consists of a prediction step and a filter step. The approximation approach is based on a systematic minimization of a distance measure and is hence optimal and deterministic. In contrast to non-determ...

In this paper we show how to derive the mean and variance of the transilluminated signal obtained in models of light propagation in tissue, based both on a stochastic Monte Carlo method and on a deterministic diffusion approximation. The theoretical treatment of the Monte Carlo model applies only to integrated intensity measurements, whereas the diffusion approximation gives an estimator for th...

We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time nonlinear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form yt = f(yt−1, . . . , yt−L), the prediction of y at time t + k is based on the estimates ŷt+k−1, . . ....

چکیده در این مطالعه، تقاضای گروه های اصلی خوراکی در مناطق شهری ایران برای دوره زمانی1361 تا 1386 بررسی شده است. بدین منظور از سیستم تقاضای تقریباً ایده آل خطی (la/aids)، شاخص تقریب خطی لاسپیرس و روش رگرسیون های به ظاهر نامرتبط (sur) استفاده شد. نتایج به دست آمده نشان داد که متغیر متوسط جمعیت خانوار در بیشتر معادلات تأثیر معناداری بر تقاضای خانوار داشته است. قیود همگنی و تقارن نیز مورد آزمون قرار...

We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to establish dependencies between output variables, where each latent function is represented as a GP. Based on these latent functions, we establish an approximation scheme using a conditional independence assumption between t...