• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.9
• /
• pp.1680-1685
• /
• 2010

In this note, a proof of Utkin's theorem is presented for a MI(Multi Input) uncertain linear case. The invariance theorem with respect to the two transformation methods so called the two diagonalization methods are proved clearly and comparatively for MI uncertain linear systems. With respect to the sliding surface transformation and the control input transformation, the equation of the sliding mode i.e., the sliding surface is invariant. Both control inputs have the same gains. By means of the two transformation methods the same results can be obtained. Through an illustrative example and simulation study, the usefulness of the main results is verified.

• The Korean Journal of Applied Statistics
• /
• v.33 no.1
• /
• pp.1-10
• /
• 2020

We propose a unified approach to variable selection, transformation and outliers in the linear model. The procedure includes a sequential method for outlier detection and a least trimmed squares estimator for variable transformation. It uses all possible subsets regressions for model selection. Some real data analyses and the simulation results are provided to show the efficiency of the methods in the context of the correct variable selection and the fitness of the estimated model.

• MALSORI
• /
• no.43
• /
• pp.127-136
• /
• 2002

The speaker adaptation technique is generally used to reduce the speaker difference in speech recognition. In this work, we focus on the features fitted to a linear regression-based speaker adaptation. These are obtained by feature transformation based on independent component analysis (ICA), and the transformation matrix is learned from a speaker independent training data. When the amount of data is small, however, it is necessary to adjust the ICA-based transformation matrix estimated from a new speaker utterance. To cope with this problem, we propose a smoothing method: through a linear interpolation between the speaker-independent (SI) feature transformation matrix and the speaker-dependent (SD) feature transformation matrix. We observed that the proposed technique is effective to adaptation performance.

• MALSORI
• /
• no.65
• /
• pp.67-80
• /
• 2008

We have been building a text-independent speaker recognition system that is robust to unknown channel and noise environments. In this paper, we propose a linear transformation to obtain robust features. The transformation is optimized to maximize the distances between the Gaussian mixtures. We use rotation of the axes, to cope with the problem of scaling the transformation matrix. The proposed transformation is similar to PCA or LDA, but can achieve better result in some special cases where PCA and LDA can not work properly. We use YOHO database to evaluate the proposed method and compare the result with PCA and LDA. The results show that the proposed method outperforms all the baseline, PCA and LDA.

• Journal of the Korean Society of Radiology
• /
• v.13 no.4
• /
• pp.509-516
• /
• 2019

In the linear transformation method, the original image is divided into a plurality of range blocks, and a partial transform system for finding an optimal domain block existing in the image for each range block is used to adjust the performance of the compression ratio and the picture quality, The nonlinear transformation method uses only the rotation transformation among eight shuffle transforms. Since the search is performed only in the limited domain block, the coding time is faster than the linear transformation method of searching the domain block for any block in the image, Since the optimal domain block for the range block can not be selected in the image, the performance may be lower than other methods. Therefore, the nonlinear transformation method improves the performance by increasing the approximation degree of the brightness coefficient conversion instead of selecting the optimal domain block, The smaller the size of the block, the higher the PSNR value, The higher the compression ratio is increased groups were quadtree block divided to encode the image at best.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.1
• /
• pp.1-9
• /
• 1998

This paper is focussed on the problem of robustly stabilizing a transformable linear time-varying system. The considered system is a class of state feedback transformable linear systems. First, the real linear time-varying system is transformed into the linear time invariant system composed with the time-invariant linear part and the time-varying uncertainty part. Second, the solution to a quadratic stabilization problem in the transformed linear system is give via' Lyapunov methods. Then this solution is used to construct a stabilizing linear control law for the real linear time-varying system.

• 전자공학회논문지 IE
• /
• v.44 no.3
• /
• pp.51-55
• /
• 2007

In this paper, we consider the controllability and observability for the time-varying linear system using the input-state(I/O), input-output(I/O) transformation and get the time-invarying linear system. The transformed system represent the system with the multiple integral. We verify the proposal algorithm via the example and examine.

• Proceedings of the KSPS conference
• /
• 2005.04a
• /
• pp.53-56
• /
• 2005

In this paper, we propose a transformation based robust adaptation technique that uses the maximum mutual information(MMI) estimation for the objective function and the linear spectral transformation(LST) for adaptation. LST is an adaptation method that deals with environmental noises in the linear spectral domain, so that a small number of parameters can be used for fast adaptation. The proposed technique is called MMI-LST, and evaluated on TIMIT and FFMTIMIT corpora to show that it is advantageous when only a small amount of adaptation speech is used.

• The Korean Journal of Applied Statistics
• /
• v.6 no.2
• /
• pp.253-263
• /
• 1993

Recent interest in Taguchi's methods have led to developments of joint modelling of the mean and dispersion in generalized linear models. Since a single data transformation cannot produce all the necessary conditions for an analysis, for the analysis of the Taguchi data, the use of the generalized linear models is preferred to a commonly used data transformation method. In this paper, we will illustrate this point and provide GLIM macros to implement the joint modelling of the mean and dispersion in generalized linear models.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.4
• /
• pp.197-205
• /
• 2019

In this paper, an efficient single dehazing algorithm is proposed based on linear transformation by assuming that a linear relationship exists in saturation component between the haze image and haze-free image. First, we analyze the linearity of saturation channel, estimate the medium transmission map in terms of the saturation component. Then, the intensity of haze-free image is assumed by using CLAHE to enhance contrast of haze image. Experimental results demonstrate that proposed algorithm can naturally recover the image, especially can remove color distortion caused by conventional methods. Therefore, our approach is competitive with other state-of-the art single dehazing methods.