• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.227-231
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• 2004

In this paper, a robust Sliding Mode Variable Structure (SMVS) controller is designed for Active Queue Management (AQM). This type of controller is insensitive to noise and variance of the parameters, thus it is suitable to time varying network systems. Simulation results conform the robust performance of SMVS controller against the disturbance. At the same time, a complete comparison between SMVS and PI controllers is made. The conclusion is that both transient and steady state performance of SMVS controller is better than that of PI one.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.255-260
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• 1988

A robust adaptive control method for a stable nonminimum phase SISO system with unmodelled dynamics is proposed. The robust parameter estimation method of the system with bounded output noise and unmodelled dynamics is employed and a parallel structure is proposed to improve the robustness of adaptive control system. The local stability of the proposed system is shown. Computer simulations are done in order to compare the performance of the proposed structure with the basic structure on various circumstance.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.135-138
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• 1987

A method for designing a robust tracking controller for linear discrete systems is investigated. Only the observable variables are to be used in the controller synthesis. To insure the robustness, the system is augmented by a compensator at the output side. Then a feedback controller is designed using delayed values of the observable variables for the augmented system. The delay times are chosen to minimize the effect of measurement accuracy and/or noise.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.10-13
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• 1998

We propose a robust non-speech rejection algorithm using the three types of pitch-related parameters. The robust non-speech rejection algorithm utilizes three kinds of pitch parameters : (1) pitch range, (2) difference of the successive pitch range, and (3) the number of successive pitches satisfying constraints related with the previous two parameters. The acceptance rate of the speech commands was 95% for -2.8dB signal-to-noise ratio (SNR) speech database that consisted of 2440 utterances. The rejection rate of the non-speech sounds was 100% while the acceptance rate of the speech commands was 97% in an office environment.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.739-741
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• 2003

Electroencephalogram (EEG)-based brain computer interface (BCI) provides a new communication channel between human brain and computer. EEG is very noisy data and contains artifacts, thus the extraction of features that are robust to noise and artifacts is important. In this paper we present a method with employ both independent component analysis (ICA) and oriented principal component analysis (OPCA) for artifact-robust feature extraction.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.142-157
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• 1996

Robust design in industry is an approach to reducing performance variation of quality characteristic values in products and processes. In the Taguchi type robust design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. In this paper, for the combined array approach to assign control and noise factors, we propose how to simultaneously optimize multiple quality characteristics. Two examples are illustrated to show the difference between the product-array approach and the combined-array approach.

• MALSORI
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• no.50
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• pp.71-83
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• 2004

Recently, broadcast news speech recognition has become one of the most attractive research areas. If we can transcribe automatically the broadcast news and store their contents in the text form instead of the video or audio signal itself, it will be much easier for us to search for the multimedia databases to obtain what we need. However, the desirable speech signal in the broadcast news are usually affected by the interfering signals such as the background noise and/or the music. Also, the speech of the reporter who is speaking over the telephone or with the ill-conditioned microphone is severely distorted by the channel effect. The interfered or distorted speech may be the main reason for the poor performance in the broadcast news speech recognition. In this paper, we investigated some methods to cope with the problems and we could see some performance improvements in the noisy broadcast news speech recognition.

• MALSORI
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• no.62
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• pp.85-96
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• 2007

In this paper, we carried out recognition experiments for noisy speech having various levels of car noise and output of an audio system using the speech interface. The speech interface consists of three parts: pre-processing, acoustic echo canceller, post-processing. First, a high pass filter is employed as a pre-processing part to remove some engine noises. Then, an echo canceller implemented by using an FIR-type filter with an NLMS adaptive algorithm is used to remove the music or speech coming from the audio system in a car. As a last part, the MMSE-STSA based speech enhancement method is applied to the out of the echo canceller to remove the residual noise further. For recognition experiments, we generated test signals by adding music to the car noisy speech from Aurora 2 database. The HTK-based continuous HMM system is constructed for a recognition system. Experimental results show that the proposed speech interface is very promising for robust speech recognition in a noisy car environment.

• Speech Sciences
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• v.9 no.1
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• pp.39-47
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• 2002

This paper proposes an effective method to remedy the acoustic modeling problem inherent in the usual log-normal Parallel Model Composition intended for achieving robust speech recognition. In particular, the Gaussian kernels under the prescribed log-normal PMC cannot sufficiently express the corrupted speech distributions. The proposed scheme corrects this deficiency by judiciously selecting the 'fairly' corrupted component and by re-estimating it as a mixture of two distributions using data-driven PMC. As a result, some components become merged while equal number of components split. The determination for splitting or merging is achieved by means of measuring the similarity of the corrupted speech model to those of the clean model and the noise model. The experimental results indicate that the suggested algorithm is effective in representing the corrupted speech distributions and attains consistent improvement over various SNR and noise cases.

• MALSORI
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• no.46
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• pp.65-76
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• 2003

In this paper, we employ the adaptive comb filtering for effective noise reduction in mobile communication environment. Adaptive comb filtering is a well-known method for noise reduction, but requires correct pitch period and must be applied just in voiced speech frames. To satisfy these requirements we use two kinds of information extracted from speech packets, one of which is the pitch period information measured precisely by a speech coder and the other is the frame rate information related to a decision on speech or silence frame. Experiments on speech recognition system confirm the efficiency of this method. Feature parameters employing this method give superior performance in noise environment to those extracted directly from output speech.