• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.719-726
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• 1987

In this paper, an adaptive IIR (infinite impulse response) notch filter of lattice type is constructed and its adaptation algorithm is proposed for the detection and retrieval of a sine wave signal embedded in noise. A modified method which adapts only one coefficient of the filter is also suggested. All these methods adapt the coefficients while keepting the poles of the filter inside the unit circle on z-plane, and thus they satisfy the condition on the stability of the IIR filter after it has converged. To investigate the convergence characteristics of these methods such as convergence speed and output S/N ratio, intensive computer simulation has been performed by varying the frequency of the sine wave and the input S/N ratio. And the results of the simulation have been compared to those of Rao and Kung's which shows relatively fast convergence speed. The methods proposed here, especially the second one. shows faster convergence speed and higher output S/N ratio than the Rao and Kung's.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.13-16
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• 2002

In this paper, we newly propose a predictor model which is a method to overcome the time-varying delay in a system and we verify that the predictor model is well suited for the time-delayed system and improves the stability a lot through the experiments. The proposed predict compensator compensates uncertain time delays and minimizes variance of system performance. Therefore it is suitable for the control of uncertain systems and nonlinear systems that are difficult to be modeled. The simulation conditions are set for the cases of various input time delays and simulations are applied for the 2-axis robot arms which are drawing a circle on the plane. Conclusively, the proposed predict compensator represents stable properties regardless of the time delay. As a future research, we suggest to develope a robust control algorithm to compensate the random time delay which occurs in the tole-operated systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.1-7
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• 1993

This paper proposed an algorithm that extracts the optimum characteristics parameters to identify the signatures from the spectrum using 2-D FFT. The signature image input through a scanner is normalized into 250*128 pixels in the prepocessor. Normalized image is divided into block segments and each segment is transformed into space spectrum by 2-d FFT. There are several methods extracting the signature characteristic parameters from that spectrum. The result of experimentations which use the characteristic parameters extracted between $0^{\circ}and\;90^{\circ}$ in (0, 0), (63, 0) corners from 64$\times$64 block spectrum shows that the signature identification rate using that method gives 92.5% of successful achievement for 100 signatures, higher than the others.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.12
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• pp.198-208
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• 1995

BiCMOS circuit consist of CMOS part which constructs logic function, and bipolar part which drives output load. Test to detect stuck-open faults in BiCMOS circuit is important, since these faults do sequential behavior and are represented as transition faults. In this paper, proposes a method for efficiently detecting transistor stuck-open faults in BiCMOS circuit by transforming them into slow-to=rise transition and slow-to-fall transition. In proposed method, BiCMOS circuit is transformed into equivalent gate-level circuit by dividing it into pull-up part which make output 1, and pull-down part which make output 0. Stuck-open faults in transistor are modelled as transition fault in input line of gate level circuit which is transformed from given circuit. Faults are detceted by using pull-up part gate level circuit when expected value is '01', or using pull-down part gate level circuit when expected value is '10'. By this method, transistor stuck-open faults in BiCMOS circuit are easily detected using conventional gate level test generation algorithm for transition fault.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.6
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• pp.9-16
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• 1980

On the multivariable systems described by state equations, it is well known that the poles of the system can be arbitrarily assigned In the S- plane by some state feedback. In this paper, it is discussed that a canonical form by which the state feedback gain matrix for pole assignment may be easily obtained Is stooled and also an algorithm to fond the state feedback gain matrix is presented.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.347-353
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• 2004

Neural oscillator can be applied to oscillator systems such as analysis of image information, voice recognition and etc, Conventional learning algorithms(Neural Network or EBPA(Error Back Propagation Algorithm)) are not proper for oscillatory systems with the complicate input patterns because of its too much complex structure. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(phase locked loop) function and a simple Hebbian learning rule, Therefore, in this paper, it will introduce an technique for Recognition of the Korean Character using Phase Synchronization Neural Oscillator and will show the result of simulation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.102-114
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• 2003

The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.162-171
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• 1999

The most important part in automated transport systems is steering control for lane keeping Most of systems developed so far have used the visual information for steering control. In this study, the steering control algorithm based on visual servoing has been developed and tested by applying it on Radio Controlled(R/C) model car equipped with one CCD camera. We also demonstrated the feasibility of using it as a pre-test car before the real car experiment in developing automated vehicles. In order to solve the problem of the limited spave and load of a model car, remote-brained approach has been taken. For steering control of a model car, the PD controller which uses the look ahead offset to generate control input has been implemented and the characteristics of the controller has been explained in view of kinematics. Some experimental results have been also illustrated so as to show the control performance and stability.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.85-88
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• 2006

Many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is include in the output of a controller. In this paper, the neuro-network 2-DOF PID Controller is designed by a neural network and the gains of this controller are adjusted automatically by the back-propagation algorithm of the neural network when the response characteristic of system is changed under a condition.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.343-356
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• 1991

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. The development time and cost for implementing a high speed signal processing system can be considerably reduced because algorithm are implemented in software using commercially available digital signal processors. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach not only requires a simple interconnection network but also reduces the number of communications among the processors very much. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors in the system. A systematic scheduling method has been developed by using a processors which can be used efficiently, the methods for solving dependency problems between the processors are investigated. Implementation procedures and results for FIR, recursive (IIR), and adaptive filtering algorithms are illustrated.