• Journal of Communications and Networks
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• v.9 no.2
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• pp.185-191
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• 2007

Alpha stable distribution is better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process has no closed form of probability density function and finite second order moments. In general, Wiener filter theory is not meaningful in S$\alpha$SG environments because the expectations may be unbounded. We proposed a new adaptive recursive least p-norm Kalman filtering algorithm based on least p-norm of innovation process with infinite variances, and a new robust multiuser detection method based on least p-norm Kalman filtering. The simulation experiments show that the proposed new algorithm is more robust than the conventional Kalman filtering multiuser detection algorithm.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.197-206
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• 2011

The ability to detect online abnormal events in signals is essential in many real-world signal processing applications. In order to detect abnormal events, previously known algorithms require an explicit signal statistical model, and interpret abnormal events as statistical model abrupt changes. In general, maximum likelihood and Bayesian estimation theory to estimate well as detection methods have been used. However, the above-mentioned methods for robust and tractable model, it is not easy to estimate. More freedom to estimate how the model is needed. In this paper, we investigate a machine learning, descriptor-based approach that does not require a explicit descriptors statistical model, based on support vector machines are known to be robust statistical models and a sequential optimal algorithm online support vector machine is introduced.

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.212-216
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• 2013

As virtual reality technologies are advanced rapidly, how to render 3D objects across modalities is becoming an important issue. This study is therefore aimed to investigate human discriminability on the curvature of 3D polygonal surfaces with focusing on the vision and touch senses because they are most dominant when explore 3D shapes. For the study, we designed a psychophysical experiment using signal detection theory to determine curvature discrimination for three conditions: haptic only, visual only, and both haptic and visual. The results show that there is no statistically significant difference among the conditions although the threshold in the haptic condition is the lowest. The results also indicate that rendering using both visual and haptic channels could degrade the performance of discrimination on a 3D global shape. These results must be considered when a multimodal rendering system is designed in near future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.286-294
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• 1990

The objective of this paper lies in presenting in theory an interpretation of how signals are detected from the real-time A/O correlator, and scrutinize by experimental processes, thereby to devise a method by which correlation function can be detected in a favorable way in time. An A/O system for real-time correlation function of two signals has been constructed. This optical correlator when at work in intensity modulation mode by acousto- optic device renders higher output signal to noise ration, as compared with the traditional optical signal detection, has simple system as compared with existing optical correlator in amplitude modulation mode.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.69-71
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• 1994

The objective of this paper is to present a systematic approach to detect and classify automatically Power Quality Disturbances by applying the recent advances in digital signal processing techniques including wavelet theory and neural networks. To demonstrate the validity of the derived result, computer simulation results are included.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3256-3263
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• 2021

The main steam line break accident is an essential initiating event of the pressurized water reactor. In present work, the fuzzy set theory and the signal-based fault detection method has been used to detect the occurrence and diagnosis of the location and break area for the small scale MSLB. The models are validated by the AP1000 accident simulator based on MAAP5. From the test results it can be seen that the proposed approach has a rapid and proper response on accident detection and location diagnosis. The method proposed to evaluate the break area shows good performances for small scale MSLB with the relative deviation within ±3%.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.282-282
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• 2000

The analysis of the radiation effect on matter has been performed using stochastic methods. Recently, It was discovered that the detector pulses of radiation can be analysed using deterministic method that utilizes the chaotic behaviour with an attractor found in a noise region. We acquired a time series for pulse tram of Am-241 using scintillation detector and reconstructed a phase space, then performed new analysis for the radiation detection signal by applying embedding theory, Lyapunov exponent, correlation dimension, autocorrelation dimension, and power spectrum.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.789-795
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• 1992

The generalized Neyman-Pearson lemma Is reformulated In the framework of the fuzzy set theory. Based on the result, we define the locally optimum fuzzy test and derive the locally optimum fuzzy test function. As a pratical application of the locally optimum fuzzy test, detection of weak deterministic signals corrupted by purely-adative noise Is considered, which Is an important problem In statistical signal processing. Comparisons between the locally optimum and the locally optimum fuzzy tests are also made.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.903-912
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• 2007

Faults of rotating parts of a train normally generate unexpected frequency band or impulsive sound[1] which has a period when it moves with a constant speed. The former can be detected by the moving frame acoustic holography method, which visualizes sound field that is generated by a moving and emitting pure tone or band limited noise source. We have attempted to apply the method to the latter case: the periodic impulsive sound which generate different signal compared with what can be measured by the band limited noise. The signal to noise ratio which determines the success of early fault detection must also be studied with the impulsive and moving signal. This research shows how the problems related with these issues can be resolved. The main idea is that periodic impulsive signal can be expressed by infinite set of discrete pure tones. This enables us to obtain lots of holograms that visualize periodic impulsive sound field including noise by using the moving frame acoustic holography method. Therefore holograms can be averaged to improve the signal to noise ratio until having reliable information that exhibits where the impulsive sources are. Theory and experiment by using the miniature vehicle are described [Work supported by BK21 & KRRI].