• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.3
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• pp.53-60
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• 2008

Recently, various recording technologies are studied for optical data storage. After standardization of BD (Blue-ray Disc) and HD-DVD (High-Definition Digital Versatile Disc), the industry is looking for a suitable technology for next generation optical data storage. Super-RENS (Super-resolution near field structure) technique, which is capable of compatibility with other systems, is one of next optical data storage. In this paper, we analyze the nonlinearity of Super-RENS read-out signal through the bicoherence test, which uses HOS (Higher-Order Statistics) and apply neural networks for nonlinear modeling. The model structure considered in this paper is the NARX (Nonlinear AutoRegressive eXogenous) model. The experiment results indicate that the read-out signals have nonlinear characteristics. In addition, it verified the possibility that neural networks can be utilized for nonlinear modeling of Super-RENS systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1606-1616
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• 2004

This paper introduces a technique for generating an appropriate template signal via modeling of minimum-phase stable ARMA (Auto-Regressive Moving Average) system for coherent impulse communication systems. It has been well known that the transmitted impulse signal becomes deformed because of dispersive and resonant characteristics. Accordingly, in spite of using ideal template signal at the correlator, these impairments degrade overall performance attributed to low level of coherence. To increase the degree of coherence, our proposed scheme realizes A3U system derived by Gaussian pulse signal, which simulates the overall characteristic of transfer function in between transmit and receive wideband antennas so as to generate an appropriate template signal in a form of output. The performance of proposed scheme will be shown in results from computer simulations to verify its affirmative impact on impulse communication system with regarding several distinctively shaped antennas.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.309-310
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• 2016

Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.156-164
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• 2000

In this study, a discrete time model for a simplified front wheel suspension system which has nonlinear dampling and stiffness property is introduced. The model is estimated from the discrete data which are generated based on the real car parameter. The performance of the proposed method is evaluated through numerical simulation, and the simulation results show that the proposed method can estimate the nonlinear behavior of the suspension system very well.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.40-52
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• 1998

Among the non-traditional machining methods, Abrasive waterjet machining process shows big promise in drilling difficult-to-machine materials due to its numerous advantages such as absence of heat affect zone and thermal distortion. Acoustic emission signal technique is used to understand about material removal mechanisms during abrasive waterjet drilling process. More information about the drilling process is derived through frequency decomposition of auto regressive moving average modeling representing acoustic emission signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.561-570
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• 2009

Ultra-wideband communication systems based on impulse radio have merits that are possible for the high data rate transmission, high resolution ranging are positioning system. Conventionally, in order to accomplish these features, the high-speed ADC (Analog to Digital Convertor) is necessary to apply radio determination system operating in time domain. However, considering low rate - wireless personal area network (LR-WPAN) aims to low-cost hardware implementation, the expensive ADC converting GHz sampling per second is not appropriate. So, this paper introduces a low complex AR (Auto Regressive) model based non-coherent ranging scheme operating in frequency domain with using low-speed ADC utilizing analog Voltage Control Oscillator (VCO) mode for the frequency domain transformation. To verify the superiority of the proposed ranging and location algorithm working in frequency domain, the suggested IEEE 802.15.4a TG channel model is used to exploit affirmative features of the proposed algorithm with conducting the simulation results.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.4
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• pp.462-470
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• 2012

The availability and efficient use of the feed resources in India are the primary drivers to maximize productivity of Indian livestock. Feed security is vital to the livestock management, extent of use, conservation and productivity enhancement. Assessment and forecasting of livestock feed resources are most important for effective planning and policy making. In the present study, 40 years of data on crop production, land use pattern, rainfall, its deviation from normal, area under crop and yield of crop were collected and modeled to forecast the likely production of feed resources for the next 20 years. The higher order auto-regressive (AR) models were used to develop efficient forecasting models. Use of climatic variables (actual rainfall and its deviation from normal) in combination with non-climatic factors like area under each crop, yield of crop, lag period etc., increased the efficiency of forecasting models. From the best fitting models, the current total dry matter (DM) availability in India was estimated to be 510.6 million tonnes (mt) comprising of 47.2 mt from concentrates, 319.6 mt from crop residues and 143.8 mt from greens. The availability of DM from dry fodder, green fodder and concentrates is forecasted at 409.4, 135.6 and 61.2 mt, respectively, for 2030.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.