• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1413-1421
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• 1993

It is possible to weaken the undesirable effect of a bounded control input signal to the plant and done by setting up an additional correction loop which compensates for the suppresed portion of the control input signal. The design and analysys of stability of state controller is used by the Kalman-Szego-Lemma and as the result of this method is made possible to take advantage of the control input to the plant even for small error signals.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.10-21
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• 1993

Bilinear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients compared with Volterra models. But bilinear filters have stability problem because they involve nonlinear feedback. Adaptive algorithms for bilinear filters may be diverge and have poor convergence characteristics when input signal is large In this paper, necessary and sufficient condition for mean square stability of bilinear filters for given input signal statistics is briefly described, and the method obtaining the input bound to guarantee the stability of bilinear filters is presented. New RPEM algorithm, which does not diverge and has the superior convergence characteristics compared with the conventional RPEM algorithm when input signal is large, is derived by applying the time-varying Kalman filtering concept to the conventional RPEM algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.90-94
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• 2008

It is well-blown that the convergence rate gets worse when an input signal to an adaptive filter is correlated. In this paper we propose a new adaptive filtering algorithm that makes the convergence rate much improved even for highly correlated input signals. By introducing an orthogonal constraint between successive input signal vectors we overcome the slow convergence problem of the LMS algorithm with the correlated input signal. Simulation results show that the proposed algerian yields fast convergence speed and excellent tracking capability under both time-invariant and time-varying environments, while keeping both computation and implementation simple.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1722-1727
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• 1992

In this study, techniques of adaptive input-output linearizing control of a class of uncertain nonlinear system are investigated. It is shown through concepts of signal growth rates that bounded trackings yield by adaptive input-output linearizing control law using normalized estimator. The convergence characteristics are improved significantly by using the normalized estimator. Simple example is presented as illustration.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.2004-2007
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• 2002

In the linear combination type stereophonic echo canceller, it is known not to converge the coefficient vector of the adaptive filter to a correct echo path. In this report, we analyze the convergence value of the filter coefficient vector of the stereo echo canceling algorithm using input signals of all channels in relation to this problem. In this analysis, one of the two inputs to the un-known system and adaptive one are assumed to be a delayed and attenuated version of the other signal as a model of the input signal with a strong cross-correlation. As a result, it is shown for the coefficient vectors not to converge to echo paths, and nor to converge to the value which depends on the time delay and the attenuation of the input signal. We show that the computer simulation result are corresponding to our analytical results.

• Journal of Navigation and Port Research
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• v.32 no.2
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• pp.133-140
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• 2008

In this paper, a fault detection method for operator failures using the observation technique is proposed. The suggested algorithm is extended using the conventional sensor/actuator fault detection method. First, it is assumed that operator failure affects human work operations, as it is an external input signal. With this assumption, a human work model with operator failure is suggested. Second, an unknown input observer with proportional and integral gains is introduced. The characteristic of this observer of estimating an external signal without an exact input is shown, and the conditions for the detection of an operator failure are proposed. Finally, by simulating the container crane operations, it is verified that the observer can accurately detect an operator failure and estimate its magnitude from the given internal signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.149-158
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• 2015

This paper proposes a subband filtering technique to the MUSIC and the ESPRIT algorithm for estimating the magnitude and frequency of the harmonics of power signal. In proposed method, the input power signal is decomposed to the odd harmonics and the even harmonics respectively by the filter bank system. The amplitude and the frequency estimation of the decomposed harmonics are carried out using the MUSIC and the ESPRIT method. Subband filtering can reduce the autocorrelation matrix size of input data, and spectrum leakage between adjacent harmonics. Therefore, this subband technique has advantage in computational cost and estimation accuracy compared to fullband MUSIC and ESPRIT. To demonstrate the performance of the method, computer simulations are performed to the synthesized input signal, and experiment results are compared in subband and fullband cases.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.78-85
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• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.91-98
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• 2004

Human uses level difference and time difference to get space information. Therefore this paper shows that method to presume direction of sound source by time difference and to mark presumed position. The position means direction from geometrical center of sensors to the sound source. To get the time difference of microphones input level, we will be explained about arrangement of microphones which used for the sensor to take the sound signal. It is included distance among the 3 microphones and distance between microphones and sound source. Secondly, input signals are transmitted to CPU througth digital process. CPU is used to DSP(Digital Signal Processor) for manage the signal by real time. Finally, the position of sound source is perceived by an explained algorithm in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.57-58
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• 2014

Digital filter is very important role in signal processing system. In general, input signal is determined by transfer function of the digital filter. But if input signal was exposured in various sound environment, it is difficult to verify its original source. In this paper, inverse problem in order to extract original input signal from noisy environment is considered.