• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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• pp.1326-1337
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• 1995

In this paper, we transformed the bilinear filter into an equivalent linear multichannel filter and derived QR decomposition based recursive least squares algorithms for bilinear lattice filters. We also defined order update relation of the forward and the backward input vectors by using the channel decomposition. The forward and the backward data matrices were defined by using the forward and the backward input vectors and orthogonalized with the QR decomposition. we can obtain the lattice equations of the bilinear filters by using the channel decomposition. we can be derived the lattice equations of the bilinear filters using this decomposition process which are the same as the lattice equations derived by Baik, we can use the coefficient transformation algorithm proposed by Baik. We derived the equation error and the output error algorithm of the QRD based RLS bilinear lattice algorithm. Also, we evaluated the performance of the proposed algorithms through the system identification of the bilinear system.

• Journal of IKEEE
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• v.21 no.2
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• pp.130-135
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• 2017

Normally, in data transmission, extra parity bits are added to the input message which were derived from its input and a pre-defined algorithm. The same algorithm is used by the receiver to check the consistency of the delivered information, to determine if it is corrupted or not. It recovers and compares the received information, to provide matching and correcting the corrupted transmitted bits if there is any. This paper aims the following objectives: to use an alternative error detection-correction method, to lessens both the fixed number of the required redundancy bits 'r' in cyclic redundancy checking (CRC) because of the required polynomial generator and the overhead of interspersing the r in Hamming code. The experimental results were synthesized using Xilinx Virtex-5 FPGA and showed a significant increase in both the transmission rate and detection of random errors. Moreover, this proposal can be a better option for detecting and correcting errors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.12
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• pp.88-96
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• 2015

This paper describes a new method for enhancing the accuracy of network analysis applications in energy management systems. Topology processing, state estimation, power flow analysis, and contingency analysis play a key factor in the stable and reliable operation of power systems. In this respect, the aim of topology processing is to provide the electrical buses and the electrical islands with the actual state of the power system as input data. The results of topology processing is used to input of other applications. New method, which includes the topology error analysis based on inconsistency check, coherency check, bus mismatch check, and outaged device check is proposed to enhance the accuracy of network analysis. The proposed methodology is conducted by energy management systems and the Korean power systems have been utilized for the test systems.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.385-390
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• 2011

In this paper, various ultra-wideband (UWB) spatial multiplxing (SM) multiple input multiple output (MIMO) receivers based on a prerake diversity combining scheme are discussed and their performance is analyzed. Several UWB MIMO detection approaches such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC), sorted QR decomposition (SQRD), and maximum likelihood (ML) are considered in order to cope with inter-channel interference. The UWB SM systems based on transmitter-side multipath preprocessing and receiver-side MIMO detection can either boost the transmission data rate or offer significant diversity gain and improved BER performance. The error performance and complexity of linear and nonlinear detection algorithms are comparatively studied on a lognormal multipath fading channel.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.48-52
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• 2001

In this paper presents an accurate AFM used that is free from the Z-directional distortion of a servo actuator is described. Two mathematical correction methods by the in-situ self-calibrationare employed in this AFM. One is the method by the integration, and the other is the method by inverse function of the calibration curve. The in situ self-calibration method by the integration, the derivative of the calibration curve function of the PZT actuator is calculated from the profile measurement data sets which are obtained by repeating measurements after a small Z-directional shift. Input displacement at each sampling point is approximately estimated first by using a straight calibration line. The derivative is integrated with reference to the approximate input to obtain the approximate calibration curve. Then the approximation of the input value of each sampling point is improved using the obtained calibration curve. Next the integral of the derivative is improved using the newly estimated input values. As a result of repeating these improving process, the calibration curve converges to the correct one, and the distortion of the AFM image can be corrected. In the in situ self-calibration through evaluating the inverse function of the calibration curve, the profile measurement data sets were used during the data processing technique. Principles and experimental results of the two methods are presented.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.627-640
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• 2018

Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.24-35
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• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.383-386
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• 1997

In this paper, We proposed a parallel structure of the Neural Network model to nonlinear complex system. Neural Network was used as basic model which has learning ability and high tolerence level. This paper, we used Neural Network which has BP(Error Back Propagation Algorithm) model. But it sometimes has difficulty to append characteristic of input data to nonlinear system. So that, I used HCM(hard c-Means) method of clustering technique to append property of input data. Clustering Algorithms are used extensively not only to organized categorize data, but are also useful for data compression and model construction. Gas furance, a sewage treatment process are used to evaluate the performance of the proposed model and then obtained higher accuracy than other previous medels.

• Current Optics and Photonics
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• v.1 no.4
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• pp.289-294
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• 2017

A high-performance time-division multiplexing (TDM) -based multiuser (MU) multiple-input multipleoutput (MIMO) system for efficient indoor visible-light communication (VLC) is presented. In this work, a MIMO technique based on RGB light-emitting diodes (LEDs) with selection combining (SC) is utilized for data transmission. That is, the proposed scheme employs RGB LEDs for parallel transmission of user data and transmits MU data in predefined slots of a time frame with a simple and efficient design, to schedule the transmission times for multiple users. Simulation results demonstrate that the proposed scheme offers an approximately 6 dB gain in signal-to-noise ratio (SNR) at a bit error rate (BER) of $3{\times}10^{-5}$, as compared to conventional MU single-input single-output (SISO) systems. Moreover, a data rate of 66.7 Mbps/user at a BER of $10^{-3}$ is achieved for 10 users in indoor VLC environments.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.