نتایج جستجو برای: Estimation theory

تعداد نتایج: 1016348  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه بیرجند 1387

چکیده ندارد.

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه شهید بهشتی - دانشکده علوم ریاضی 1387

چکیده ندارد.

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه رازی - دانشکده علوم 1388

چکیده ندارد.

Journal: :amirkabir international journal of electrical & electronics engineering 2014
i. kalantari b. zakeri

polarimetric synthetic aperture radar (pol.-sar) allows us to implement the recognition and classification of radar targets. this article investigates the arrangement of scatterers by sar data and proposes a new look-up table of region (ltr). this look-up table is based on the combination of (entropy h/anisotropy a) and (anisotropy a/scattering mechanism α), which has not been reported up now. ...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تهران 1387

چکیده ندارد.

Journal: :Springer Actuarial 2022

Abstract This chapter is on classical statistical decision theory. It an important for historical reasons, but it also provides the right mathematical grounding and intuition more modern tools from data science machine learning. In particular, we discuss maximum likelihood estimation (MLE), unbiasedness, consistency asymptotic normality of MLEs in this chapter.

In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

2006
Christos Dimitrakakis

This tutorial examines simple physical models of vehicle dynamics and overviews methods for parameter estimation and control. Firstly, techniques for the estimation of parameters that deal with constraints are detailed. Secondly, methods for controlling the system are explained.

2002
Eun-Young Elaine Kang Isaac Cohen Gérard G. Medioni

Robustness of parameter estimation relies on discriminating inliers from outliers within the set of correspondences. In this paper, we present a method using tensor voting to eliminate outliers and estimating affine transformation parameters directly from covariance matrix of selected inliers without additional parameter estimation processing. Our approach is based on the representation of the ...

Journal: :Banach Center Publications 1997

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