• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.983-987
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• 2004

Pilot symbol assisted modulation (PSAM) can be used for the channel estimation. However, imperfect channel estimates degrade the bit error rate (BER) performance. I derive the exact BER of 16-level quadrature amplitude modulated (16-QAM) orthogonal frequency division multiplexing (OFDM) systems with PSAM in time dispersive Rayleigh fading channels. In real system, there is 2.5 dB penalty in $\overline{\gamma_b}$for the same BER relative to ideal system with perfect channel estimation.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.451-459
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• 2008

Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.49-55
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• 2017

Recently, for safety of people, there are proposed so many technologies which detect density of people at the specific place or space. The representative technology for crowd density estimation was using image analysis method from CCTV images. However, this method had a weakness which could not be used and which's accuracy was lower at the dark or smog space. Therefore, in this paper, to solve this problem, we proposed a user density estimation system at closed space using high frequency and smart device. The system send inaudible high frequencies to smart devices and it count the smart devices which detect the high frequencies on the space. We tested real-time user density with the proposed system and ten smart devices to evaluate performance. According to the testing results, we confirmed that the proposed system's accuracy was 95% and it was very useful. Thus, because the proposed system could estimate about user density at specific space exactly, it could be useful technology for safety of people and measurement of space use state at indoor space.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.7-13
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• 2017

We consider a distributed estimation where many nodes remotely placed at known locations collect the measurements of the parameter of interest, quantize these measurements, and transmit the quantized data to a fusion node; this fusion node performs the parameter estimation. Noting that quantizers at nodes should operate in a non-regular framework where multiple codewords or quantization partitions can be mapped from a single measurement to improve the system performance, we propose a low-weight estimation algorithm that finds the most feasible combination of codewords. This combination is found by computing the weighted sum of the possible combinations whose weights are obtained by counting their occurrence in a learning process. Otherwise, tremendous complexity will be inevitable due to multiple codewords or partitions interpreted from non-regular quantized data. We conduct extensive experiments to demonstrate that the proposed algorithm provides a statistically significant performance gain with low complexity as compared to typical estimation techniques.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.185-188
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• 1999

An estimation algorithm for vehicle driving load has been proposed in this paper. Driving load is an important factor in a vehicle's longitudinal motion control. An approach using an observer is introduced to estimate driving load based on inexpensive RPM sensors currently being used in production vehicles. Also, a torque estimation technique using nonlinear characteristic functions has been incorporated in this estimation algorithm. Using a nonlinear full vehicle simulation model, we study the effect of the driving load on longitudinal vehicle motion, and the performance of the estimation algorithm has been evaluated. The proposed estimation algorithm has good performance and robustness over uncertainties in the system parameters. An accurate estimate of the driving load can be very helpful in the development of advance vehicle control systems such as intelligent cruise control systems, CW/CA systems and smooth shift control systems.

• Journal of electromagnetic engineering and science
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• v.6 no.4
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• pp.203-208
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• 2006

Channel estimation and data detection for OFDM systems over time- and frequency-selective channels are investigated. Relying on the complex exponential basis expansion channel model, a pilot-embedded channel estimation scheme with low computational complexity and spectral efficiency is proposed. A periodic pilot sequence is superimposed at a low power on information bearing sequence at the transmitter before modulation and transmission. The channel state information(CSI) can be estimated using the first-order statistics of the received data. In order to enhance the performance of channel estimation, we recover the transmitted data which can be exploited to estimate CSI iteratively. Simulation results show that the proposed method is suitable for doubly-selective channel estimation for the OFDM systems and the performance of the proposed method can be better than that of the Wiener filter method under some conditions. Through simulations, we also analyze the factors which can affect the system performances.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.33-39
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• 2019

We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.209-216
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• 2005

Performance assessment has Problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy Performance assessment system to solve problem of the conventional performance assessment. This Paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy Performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.43-49
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• 2023

In modern wireless communication systems including beamformers or location-based services (LBS), which employ multiple antenna elements, estimating the number of signals is essential for accurately determining the quality of the communication service. Representative signal number estimation algorithms including the Akaike information criterion (AIC) and minimum description length (MDL) algorithms, which are information theoretical criterion models, determine the number of signals based on a reference value that minimizes each criterion. In general, increasing the number of elements mounted onto the array antenna enhances the performance of estimating the number of signals; however, it increases the computational complexity of the estimation algorithm. In addition, various configurations of array antennas for the increased number of antenna elements should be considered to efficiently utilize them in a limited location. In this paper, we introduce an efficient signal number estimation algorithm based on the beamspace based AIC and MDL techniques that reduce the computational complexity by reducing the dimension of a uniform circular array antenna. Since this algorithm is based on a uniform circular array antenna, it presents the advantages of a circular array antenna. The performance of the proposed signal number estimation algorithm is evaluated through computer simulation examples.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.20-24
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• 1995

In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.