• Journal of the Korean Operations Research and Management Science Society
• /
• v.28 no.3
• /
• pp.61-66
• /
• 2003

In many multiple regression analyses, the “multi-collinearity” problem arises since some independent variables are highly correlated with each other. Practically, the Ridge regression method is often adopted to deal with the problems resulting from multi-collinearity. We propose a better alternative method using iteration to obtain an exact least squares estimator. We prove the solvability of the proposed algorithm mathematically and then compare our method with the traditional one.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.5
• /
• pp.959-965
• /
• 2010

For multiclassification, it is often the case that some variables are not important while some variables are more important than others. We propose a novel algorithm for selecting such relevant variables for multiclassification. This algorithm is base on multiclass least squares support vector machine (LS-SVM), which uses results of multiclass LS-SVM using one-vs-all method. Experimental results are then presented which indicate the performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.134-136
• /
• 1986

In this paper, a new power spectral estimation technique is presented. At first, by transforming the original data with the Karhunen-Loeve Transform(KLT), we can reduce the amount of the redundant information. Next, by modeling the transformed data by means of the autoregressive(AR) model and then applying the least-squares parameter estimation algorithm to this model, even more accurate spectrum estimates can be obtained. The KLT is the optimum transform for signal representation with respect to the mean-square error criterion. And the least-squares method is used to overcome the inherent shortcomings of popular burg algorithm.

• Proceedings of the IEEK Conference
• /
• 2002.06a
• /
• pp.61-64
• /
• 2002

In this paper, various equalizers are considered to improve the performance of Home Phoneline Networking Alliance (HomePNA) 2.0 system under dispersive channel with intersymbol interference. We evaluate and compare the performances of Recursive Least Squares (RLS) and Least Mean Squares (LMS) adaptation algorithms. Computer simulations show that the equalizers utilizing tile RLS algorithm outperforms the LMS algorithm, especially for the system of high symbol rate and complex constellation.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.1
• /
• pp.32-37
• /
• 2020

This paper proposes a new l₁-norm-Recursive Least Squares (RLS) algorithm which is numerically more robust than the conventional l₁-norm-RLS. The l₁-norm-RLS was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm has numerical instability in the inverse matrix calculation. In this paper, we propose a new algorithm which is robust against the numerical instability. We show that the proposed method improves stability under several numerically erroneous situations.

• Journal of the Korea Society of Computer and Information
• /
• v.1 no.1
• /
• pp.53-64
• /
• 1996

The methods for designing the adaptive filter performing DSP(digital signal processing)functions In mobile communication systems are Least-squares algorithm. Fast-Kalman and adaptive lattice algorithm. Least-squares algorithm It fast convergence algorithm for signal Processor of adaptive equallizer and used for eliminating inter symbol Interference which occur inmultiple path fading channel In mobille communication systems. In this paper. we propose the method of control adjustably algebra characteristics of signal vector that is sampling at some of new data sequence and confirm the improvement of fast convergence and iterative performance speed compared to existing algorithms by computer simulation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.7
• /
• pp.61-67
• /
• 2007

The load forecasting has been an important part of power system Accordingly, it has been proposed various methods for the load forecasting. The load patterns of the special days is quite different than those of ordinary weekdays. It is difficult to accurately forecast the load of special days due to the insufficiency of the load patterns compared with ordinary weekdays, so we have proposed fuzzy least squares linear regression algorithm for the load forecasting. In this paper we proposed four models for fuzzy least squares linear regression. It is separated by coefficients of fuzzy least squares linear regression equation. we compared model of H1 with H4 and prove it H4 has accurately forecast better than H1.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.228-236
• /
• 2014

Towed array SONAR is deformed because it operates in fluid such as an ocean. It especially undergoes significant change in shape as a towing vessel takes a turn. In this case, beam pattern synthesis of the line array is limited, resulting in degradation in quality such as signal-to-noise ratio. This paper presents a modified two-step least squares algorithm based on the two-step least squares method. The shape of the sea-operated line array formation with the towing vessel changing course(angle) was modeled and the algorithm was subsequently applied. While changing course and location of the main lobe in beam pattern was altered, signal-to-noise ratio of steering beam pattern synthesis was analyzed by algorithm (proposed and others). As a result, the proposed algorithm presented improvement in performance by 2dB compared to other algorithms while forming relatively constant beam pattern.

• Journal of Broadcast Engineering
• /
• v.21 no.6
• /
• pp.920-928
• /
• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted least squares filtering with iCAM06 model. To show more perceptual high dynamic range images in conventional display, we decompose high dynamic range image into base layers and detail layers. The base layers are obtained by using weighted least squares filter. Then, we adopt chromatic adaption function and non-linear compression function to deal with base layers. Only the base layers reduce contrast, and preserving detail. The image quality assessment shows that our tone mapped image is more similar to original high dynamic range image. Moreover, the subjective result shows our algorithm produces more reliable and pleasing image.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.6
• /
• pp.246-253
• /
• 2013

Based on the conventional 2-6GHz digital frequency discriminator (DFD) using the phase unwrapping and least-squares techniques, we propose a new 2-18GHz DFD. To compensate for lowered-precision frequency estimation due to the expanded bandwidth, the proposed DFD design employs more delay lines, accordingly accompanying high complexity. Thus, a new computationally efficient frequency estimation algorithm is also presented to overcome such high computational burden. More specifically, the proposed frequency estimation algorithm is basically based on the conventional phase unwrapping technique, along with a new candidates selection for the unwrapped phases under the condition that the phase margin is known. As a result, the computational burden required for the least-squares technique can be reduced. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach, compared with those of the conventional DFD's.