نتایج جستجو برای: least squares technique
تعداد نتایج: 980837 فیلتر نتایج به سال:
Abstract: Determination of the diffusion coefficient on the base of solution of a linear inverse problem of the parameter estimation using the Least-square method is presented in this research. For this propose a set of temperature measurements at a single sensor location inside the heat conducting body was considered. The corresponding direct problem was then solved by the application of the ...
Determining the diffusion coefficient based on the solution of the linear inverse problem of the parameter estimation by using the Least-square method is presented. A set of temperature measurements at a single sensor location inside the heat conducting body is required. The corresponding direct problem will be solved by an application of the heat fundamental solution.
In this paper, a new method for gray-scale image and color zooming algorithm based on their local information is offered. In the proposed method, the unknown values of the new pixels on the image are computed by Moving Least Square (MLS) approximation based on both the quadratic spline and Gaussian-type weight functions. The numerical results showed that this method is more preferable to biline...
A recent study on the condition numbers of mixed least squares-total squares (MTLS) problem is due to Zheng and Yang (Numer Linear Algebra Appl. 2019;26(4):e2239). However, associated expressions are not compact Kronecker-product operations make computation costly. In this paper, we first present new alternative closed formula for order perturbation estimate MTLS solution. Then reveal relations...
در این پایان نامه کاهش مرتبه سیستم های مرتبه بالای خطی غیر متغیر با زمان مورد بررسی قرار می گیرد. کاهش مرتبه سیستم ها راهی برای کاهش پیچیدگی آن ها است به طوری که هزینه های بهره برداری، نگهداری، تعمیرات آن ها و همچنین هزینه های طراحی کنترل کننده برای آن ها به میزان قابل توجهی کاهش یابد. از جمله روش هایی که جهت کاهش مرتبه سیستم ها تاکنون ارائه شده اند، روش های تحقق بالانس شده (وانواع آن) و تقریب ...
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