نتایج جستجو برای: which is estimated using covariance function

تعداد نتایج: 9339917  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه فردوسی مشهد 1388

abstract following innovations in the field of elt, a new topic which has recently attracted a lot of attention is metaphor analysis. although this area of research is still in its infancy in elt, it seems that the idea can shed more light on the puzzle of english language learning and teaching. therefore, the major aim of this study is to analyze language learning and teaching in formal a...

2007
D. Richmond

A classical problem in many radar and sonar applications is the adaptive detection/esti-mation of a given signal in the presence of zero mean Gaussian noise. Reed, Mallett, and Brennan (RMB) derived and analyzed an adaptive detection scheme where the noise adaptation and non-trivial nature of their analysis resulted from the use of a noise sample covariance matrix (SCM). The case now considered...

Abstract: In this paper, we fit a function on probability density curve representing an information stream using artificial neural network . This methodology result is a specific function which represent a memorize able probability density curve . we then use the resulting function for information compression by Huffman algorithm . the difference between the proposed me then with the general me...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی خواجه نصیرالدین طوسی - دانشکده برق و کامپیوتر 1391

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

Journal: :IEEE Control Systems Letters 2023

Applying regularization in reproducing kernel Hilbert spaces has been successful linear system identification using stable designs. From a Gaussian process perspective, it automatically provides probabilistic error bounds for the identified models from posterior covariance, which are useful robust and stochastic control. However, require knowledge of true hyperparameters design. They can be ina...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه پیام نور - دانشگاه پیام نور استان تهران - دانشکده علوم ریاضی و مهندسی کامپیوتر 1392

heuristics are often used to provide solutions for flow shop scheduling problems.the performance of a heuristic is usually judged by comparing solutions and run times on test cases.this investigation proposes an analytical alternative ,called asymptotic convergence ,which tests the convergence of the heuristic to a lower bound as problem size grows. the test is a stronger variation of worst cas...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه فردوسی مشهد 1376

in this thesis our aim is to construct vector field in r3 for which the corresponding one-dimensional maps have certain discontinuities. two kinds of vector fields are considered, the first the lorenz vector field, and the second originally introced here. the latter have chaotic behavior and motivate a class of one-parameter families of maps which have positive lyapunov exponents for an open in...

Journal: :Computational Statistics & Data Analysis 2016
Lajos Horváth Gregory Rice Stephen Whipple

In the analysis of functional time series an object which has seen increased use is the long run covariance function. It arises in several situations, including inference and dimension reduction techniques for high dimensional data, and new applications are being developed routinely. Given its relationship to the spectral density of finite dimensional time series, the long run covariance is nat...

Journal: :CoRR 2015
Taishan Lou

The possible methodologies to handle the uncertain parameter are reviewed. The core idea of the desensitized Kalman filter is introduced. A new cost function consisting of a posterior covariance trace and trace of a weighted norm of the state error sensitivities matrix is minimizing to obtain a well-known analytical gain matrix, which is different from the gain of the desensitized Kalman filter...

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