• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.929-936
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• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1898-1902
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• 2012

In this paper, we consider the delay-dependent robust stability condition for polytopic uncertain systems with interval time-varying delay using various combinations of quantization and overflow nonlinearities. A robust stability condition for uncertain systems with time-varying delay and quantization/overflow nonlinearities is proposed by LMI(linear matrix inequality) and Lyapunov technique. It is shown that the proposed method is less conservative compared to the recent results by numerical examples.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.46-54
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• 1998

In this paper we propose a fast adaptive image restoration filter using DCT-based block classification for reducing block artifacts in compressed images. In order to efficiently reduce block artifacts, edge direction of each block is classified by using the DCT coefficients, and the constrained least square (CLS) on the observation that the quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space-varying degradation operator. For real-time implementation, the proposed restoration filter can be realized in the form of a truncated FIR filter, which is suitable for postprocessing reconstructed images in HDTV, DVD, or video conference systems.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.213-217
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• 2017

Since more than 30% of the liquid rocket engine failures occur during the start-up process, and the Space Shuttle Main Engine (SSME) is especially sensitive to small changes in propellant conditions, a 2% error in the valve position or a 0.1sec timing error could lead to significant damage of the engine, simulation modeling of start-up process is important. However, there are many difficulties associated with engine start-up process caused by nonlinear mass flow and heat transfer characteristics associated with filling an unconditioned engine system with cryogenic propellants. In this paper, we modelled a SSME simulation model using partially Computational Fluid Dynamics (CFD) method to solve these problems and checked the performance by comparing with the performance of the simulation model using the lumped method under the state of normal condition.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.174-184
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• 2013

For the successful R&D and deployment of LED-based green energy lighting systems, the real-time power quality measurement of both various non-linear power signals including pulse waveform, spike waveform, etc and the undesired-signals including harmonics, sag, swell, etc is required. In this paper, we propose a low-cost power quality measurement (PQM) method for low- (60Hz-several KHz) to high-frequency (several tens KHz) power signals, which are generated by green-energy lighting systems, and implement a PQM testbed using TI TMS320F28335 MCU. The proposed algorithm is programmed using C in the CCS (Code Composer Studio) 3.3 environment and is verified using test signals generated by an arbitrary signal generator, NF-WF1974. In the implemented testbed, we can measure various non-linear current signals that LED SMPS generates, analyze harmonics by fast Fourier transform, and test sag, swell, and interruption using wavelet transform.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1C
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• pp.14-21
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• 2011

Cryptographic protocols based on bilinear pairings provide excellent alternatives to conventional elliptic curve cryptosystems based on discrete logarithm problems. Through active research has been done toward fast computation of the bilinear pairings, it is still believed that the computational cost of one pairing computation is heavier than the cost of one ECC scalar multiplication. However, there have been many progresses in pairing computations over binary fields. In this paper, we compare the cost of BLS signature scheme with ECDSA with equvalent level of security parameters. Analysis shows that the cost of the pairing computation is quite comparable to the cost of ECC scalar multiplication for the case of binary fields.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.179-185
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• 2010

In a sensitivity analysis, an uncertainty importance measure is often used to assess how much uncertainty of an output is attributable to the uncertainty of an input, and thus, to identify those inputs whose uncertainties need to be reduced to effectively reduce the uncertainty of output. A function is called monotonic if the output is either increasing or decreasing with respect to any of the inputs. In this paper, for a monotonic function, we propose a method for evaluating the measure which assesses the expected percentage reduction in the variance of output due to ascertaining the value of input. The proposed method can be applied to the case that the output is expressed as linear and nonlinear monotonic functions of inputs, and that the input follows symmetric and asymmetric distributions. In addition, the proposed method provides a stable uncertainty importance of each input by discretizing the distribution of input to the discrete distribution. However, the proposed method is computationally demanding since it is based on Monte Carlo simulation.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2711-2720
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• 1997

Multitasking and microtasking on the CRAY machine provides still another way to improve computational power. Since CRAY-2 has 4 processors we can achieve speedup up to 4 properly designed algorithms. In this paper we present two parallelizations of linear system solution in the CRAY-2 with multitasking and microtasking library. One is the LU decomposition on the dense matrices and the other is the iterative solution of large sparse linear systems with the preconditioner proposed by Radicati di Brozolo. In the first case we realized a speedup of 1.3 with 2 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 600 with the multitasking and in the second case a speedup of around 3 with 4 processors for a matrix of dimension 8192 with the microtasking. In the first case the speedup is limited because of the nonuniform vector lenghts. In the second case the ILU(0) preconditioner with Radicati's technique seem to realize a reasonable high speedup with 4 processors.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.