• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1073-1080
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• 2011

In this study, a target detection algorithm was proposed for using hyperspectral imagery. The proposed algorithm is designed to have minimal processing time, low false alarm rate, and flexible threshold selection. The target detection procedure can be divided into two steps. Initially, candidates of target pixel are extracted using matching ratio of spectral pattern that can be calculated by spectral derivation. Secondly, spectral distance is computed only for those candidates using Euclidean distance. The proposed two-step method showed lower false alarm rate than the Euclidean distance detector applied over the whole image. It also showed much lower processing time as compared to the Mahalanobis distance detector.

• Progress in Medical Physics
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• v.6 no.2
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• pp.103-109
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• 1995

Power spectral analysis of spontaneous heart rate fluctuations were assessed by use of autooic blocking agents and changes in posture. The total power spectral range of interest is divided amongst the various experiments so that each respiratory pattern contributes a spectral ratio of interval to respiration only over a group of frequencies for which the specific respiratory pattern has substantial, and roughly constant, spectral magnitudes. System hardware is consisted ECG preamplifier, respiratory fluctuation detect, interval time generator and IBC 486PC. High frequency fluctuation, at the respiratiory frequency, are decreased by standing and are mediated solely by the parasympathetic system. Power spectral analysis is a powerful nonivsve tool for quantitying autonomic nervous system activity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.739-746
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• 2015

Several damage counting methods can be applied for the fatigue issues of a ground vehicle system using strain data and acceleration data is partially used for a high cyclic loading case. For a vibration test, acceleration data is, however, more useful than strain one owing to the good nature of signal-to-random ratio at acceleration response. The test severity can be judged by the fatigue damage and the pseudo-damage from the acceleration response stated in ISO-16750-3 is one of sound solutions for the vibration test. The comparison of fatigue damages, derived from both acceleration and strain, are analyzed in this study to determine the best choice of fatigue damage over multi-spectral input pattern. Uniaxial excitation test was conducted for a notched simple specimen and response data, both acceleration and strain, are used for the comparison of fatigue damages.

• Journal of Biomedical Engineering Research
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• v.8 no.1
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• pp.41-48
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• 1987

In estimating the freguency-dependent attenuation coefficient, we analyzed the range-dependent ultrasonic beam and proposed the method of calculating the experimental equation of beam pattern in order to reduce the error on the influence of beam pattern. These experimental equations are divided into the spectral centroid and the spec ural standard deviation slope according to axial propagation length. These are repnesented by the first-order equation in the near field of the beam and the second- order eqLlatlon In the far field. In order to prove the validity of this method, the attenuation coefficients of the non-corrected ease and the corrected case are compared. Using the reflected signal from acryle plate, the attenuation coefficients were estimated by the spectral shift method ann the spectral difference method. The result shows attenuation coeffi talents after correction are better than attenuation coefficients before correction. And this method can be applied In vivo measurement.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.11
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• pp.840-845
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• 2014

Vibration profiles consist of two kinds of pattern, random and harmonic, at general engineering problems and the detailed vibration test mode of a target system is decided by the spectral condition that is exposed under operation. In moving mobility, random responses come generally from road source; whereas the harmonic responses are triggered from rotating machinery parts, such as combustion engine or drive shaft. Different spectral input may accumulate different damage in frequency domain since the accumulated fatigue damage dependent on the pattern of input spectrum in high cyclic loading condition. To evaluate the sensitivity of spectral damage according to different loading conditions, a linear elastic system is introduced to conduct a uniaxial vibration testing. Measured data, acceleration and strain, is analyzed using energy isocline function and then, the calculated fatigue damage is compared by different loading cases, random and harmonic.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.111-117
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• 2009

In this paper, a new speech endpoint detector in noisy environment is proposed. According to the previous research, the energy feature in the speech region is easily distinguished from that in the speech absent region. In conventional method, the endpoint can be found by applying the edge detection filter that finds the abrupt changing point in feature domain. However, since the frame energy feature is unstable in noisy environment, the accurate edge detection is not possible. Therefore, in this paper, the novel feature extraction method based on spectrum envelop pattern is proposed. Then, the edge detection filter is applied to the proposed feature for detection of the endpoint. The experiments are performed in the car noise environment and a substantial improvement was obtained over the conventional method.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.223-240
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• 1998

The purpose of this paper is to develop the pattern recognition system with a 'Robust' concept to be applicable to flexible manufacture automation in practice. The 'Robust' concept has four meanings as follows. First, pattern recognition is performed invariantly in case the object to be recognized is translated, scaled, and rotated. Second, it must have strong resistance against noise. Third, the completely learned system is adjusted flexibly regardless of new objects being added. Finally, it has to recognize objects fast. To develop the proposed system, contouring, spectral analysis and Fuzzy ART neural network are used in this study. Contouring and spectral analysis are used in preprocessing stage, and Fuzzy ART is used in object classification stage. Fuzzy ART is an unsupervised neural network for solving the stability-plasticity dilemma.