• Journal of Broadcast Engineering
• /
• v.15 no.1
• /
• pp.63-75
• /
• 2010

In this paper, the equalizer techniques that is able to adopt the digital on-channel repeater for 8VSB-based DTV system has been analyzed and we propose an effective equalizer structure which can reduce the error propagation phenomenon by the feedback signal and improve the receiver performance at the same time. In order to confirm the effective cancellation of the feedback signal, the multi-level Correlation LMS scheme is proposed through the analysis of conventional basic LMS based DFE and Correlation LMS algorithm and as compared with the conventional method, we can confirm the reduction of error propagation. When performing the computer simulation, as the Brazil channel model which is very popular for DTV broadcasting system is adopted, the result is drawn by comparing and analysing the equalizer algorithm. We have examine the symbol error rate which is in the range of 15~25dB of operation receipt SNR and MSE(Mean Square Error) in the DTV broadcasting system. As a result of comparing with the existing method, the signal-noise ratio which is necessary for maintain the bit error correction ability that the means of proposal is same is reduced by about 2~5dB, and in the rate of convergence through the MSE, we found the reduction of needed time.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.3 s.96
• /
• pp.215-221
• /
• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.3E
• /
• pp.43-46
• /
• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.

• The Korean Journal of Applied Statistics
• /
• v.27 no.3
• /
• pp.419-430
• /
• 2014

An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.3
• /
• pp.559-564
• /
• 2013

In this paper a new hybrid forecast method composed of wavelet transform and neural network is proposed to forecast the wind speed more accurately. In the field of wind energy research, accurate forecast of wind speed is a challenging task. This will influence the power system scheduling and the dynamic control of wind turbine. The wind data used here is measured at 15 minute time intervals. The performance is evaluated based on the metrics, namely, mean square error, mean absolute error, sum squared error of the proposed model and compared with the back propagation model. Simulation studies are carried out and it is reported that the proposed model outperforms the compared model based on the metrics used and conclusions were drawn appropriately.

• The Journal of Korea Robotics Society
• /
• v.17 no.1
• /
• pp.25-31
• /
• 2022

Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.4
• /
• pp.691-698
• /
• 2003

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-l, we may compute the updated estimate of this vector at iteration n upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RLS algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the B times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• Wind and Structures
• /
• v.26 no.2
• /
• pp.99-114
• /
• 2018

Due to shortage of land and architectural aesthetics, sometimes the buildings are constructed as unconventional in plan. The wind force acts differently according to the plan shape of the building. So, it is of utter importance to study wind force or, more specifically wind pressure on an unconventional plan shaped tall building. To address this issue, this paper demonstrates a comprehensive study on mean pressure coefficient of 'E' plan shaped tall building. This study has been carried out experimentally and numerically by wind tunnel test and computational fluid dynamics (CFD) simulation respectively. Mean wind pressures on all the faces of the building are predicted using wind tunnel test and CFD simulation varying wind incidence angles from $0^{\circ}$ to $180^{\circ}$ at an interval of $30^{\circ}$. The accuracy of the numerically predicted results are measured by comparing results predicted by CFD with experimental results and it seems to have a good agreement with wind tunnel results. Besides wind pressures, wind flow patterns are also obtained by CFD for all the wind incidence angles. These flow patterns predict the behavior of pressure variation on the different faces of the building. For better comparison of the results, pressure contours on all the faces are also predicted by both the methods. Finally, polynomial expressions as the sine and cosine function of wind angle are proposed for obtaining mean wind pressure coefficient on all the faces using Fourier series expansion. The accuracy of the fitted expansions are measured by sum square error, $R^2$ value and root mean square error.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.8A
• /
• pp.813-819
• /
• 2007

In this paper, the effect of a propagation delay resulting from the use of an OFDM-based cellular system with a transparent mobile multi-hop relay(MMR) is initially analyzed. Then, channel estimation techniques, a least square(LS) method and a minimum mean square error(MMSE) method, for the OFDM systems with throughput enhancement(TE) MMR or cooperative MMR are proposed. The proposed channel estimation techniques can overcome the performance degradation caused by the propagation delay in TE MMR or cooperative MMR systems. It is demonstrated by computer simulation that the proposed channel estimation techniques for OFDM systems with transparent MMR are superior to the conventional techniques in terms of mean square error(MSE) and bit error rate(BER).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.6
• /
• pp.1455-1461
• /
• 2012

MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.