• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.422-424
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• 1997

In this paper, we characterize the whole class of vector fields that can be linearized by a given nominal state transformation and a feedback linearizing controller. The necessary and sufficient condition for a given uncertain vector field to be so-called "completely linearizable by the nominal coordinate transformation" is given in terms of Lie Bracket of uncertain vector fields and some suitable vector fields of the nominal system.

• Progress in Superconductivity and Cryogenics
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• v.12 no.1
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• pp.28-31
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• 2010

A magnetic field calculation method for toroidal type winding which has circular section was developed. At first, the equation for magnetic field by single filament coil was extended using numerical integration to estimate the entire interesting region of solenoid, especially winding region itself. And then, the magnetic field by toroidal arrangement of solenoids was computed with a coordinate transformation of vector fields. The superconducting magnet with toroidal arrangement can be made up of several tens of solenoid type double pancake windings for some applications such as superconducting magnetic energy storage system(SMES). In this system, the field calculation on the high-Tc superconducting(HTS) tape itself is very important because the entire system can be reached to a fault by magnetic stress of conductor or the critical current of superconducting tape can be dramatically reduced under its self field condition. To make matters worse, 3-dimensional analysis is indispensable for this type of magnet and the most of commercial programs with finite element method can be taken too much time for analysis and design. In this paper, a magnetic field calculation method for toroidal type winding with circular section was induced.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.161-168
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• 2004

A single-index model is useful in fields which employ multidimensional regression models. Many methods have been developed in parametric and nonparametric approaches. In this paper, posterior inference is considered and a wavelet series is thought of as a function approximated to a true function in the single-index model. The posterior inference needs a prior distribution for each parameter estimated. A prior distribution of each coefficient of the wavelet series is proposed as a hierarchical distribution. A direction $\beta$ is assumed with a unit vector and affects estimate of the true function. Because of the constraint of the direction, a transformation, a spherical polar coordinate $\theta$, of the direction is required. Since the posterior distribution of the direction is unknown, we apply a Metropolis-Hastings algorithm to generate random samples of the direction. Through a Monte Carlo simulation we investigate estimates of the true function and the direction.