• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.98-106
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• 2001

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a dead beat observer that is well-known method. However it has disadvantage such as a noise amplification effect. To reduce of the effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. Although RLSM estimator is one of the most effective methods for online parameter identification, it is difficult to obtain unbiased result in this application. It is caused by disturbed dynamic model with external torque. The proposed RLSM estimator is combined with a high performance torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.285-294
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• 2001

Recently many efforts on the development of automatic processing system for delivery sequency sorting have been performed in ETRI, which requires the use of postal 4-state bar code system to encode delivery points. This paper addresses the issue on the extension of read range and the improvement of image processing method. For the improvement of image processing procedure, applied information acquisition method through basic two thresholds onto the horizontal axial line of gray image based on reference information of 4-state bar code symbology. Symbol values are computed after creating two threshold values based on the obtained information through search of horizontal axial values. The implementation result of 4-state bar code reader are obtained the symbol values within 30~60 msec (58,000~116,000 mail item/hour)without noise removal or image rotation in spite of the incline $\pm 45^{\circ}$.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.361-373
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• 2002

In this paper, we propose a channel normalization method to improve the performance of CMS (cepstral mean subtraction) which is widely adopted to normalize a channel variation for speech and speaker recognition. CMS which estimates the channel effects by averaging long-term cepstrum has a weak point that the estimated channel is biased by the formants of voiced speech which include a useful speech information. The proposed Formant-broadened Cepstral Mean Subtraction (FBCMS) is based on the facts that the formants can be found easily in log spectrum which is transformed from the cepstrum by fourier transform and the formants correspond to the dominant poles of all-pole model which is usually modeled vocal tract. The FBCMS evaluates only poles to be broadened from the log spectrum without polynomial factorization and makes a formant-broadened cepstrum by broadening the bandwidths of formant poles. We can estimate the channel cepstrum effectively by averaging formant-broadened cepstral coefficients. We performed the experiments to compare FBCMS with CMS, PFCMS using 4 simulated telephone channels. In the experiment of channel estimation, we evaluated the distance cepstrum of real channel from the cepstrum of estimated channel and found that we were able to get the mean cepstrum closer to the channel cepstrum due to an softening the bias of mean cepstrum to speech. In the experiment of text-independent speaker identification, we showed the result that the proposed method was superior than the conventional CMS and comparable to the pole-filtered CMS. Consequently, we showed the proposed method was efficiently able to normalize the channel variation based on the conventional CMS.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.335-347
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• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.26-33
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• 2008

The analysis of wide-angle seismic reflection and refraction data plays an important role in lithospheric-scale crustal structure study. However, it is extremely difficult to develop an appropriate velocity structure model directly from the observed data, and we have to improve the structure model step by step, because the crustal structure analysis is an intrinsically non-linear problem. There are several subjective processes in wide-angle crustal structure modelling, such as phase identification and trial-and-error forward modelling. Because these subjective processes in wide-angle data analysis reduce the uniqueness and credibility of the resultant models, it is important to reduce subjectivity in the analysis procedure. From this point of view, we describe two software tools, PASTEUP and MODELING, to be used for developing crustal structure models. PASTEUP is an interactive application that facilitates the plotting of record sections, analysis of wide-angle seismic data, and picking of phases. PASTEUP is equipped with various filters and analysis functions to enhance signal-to-noise ratio and to help phase identification. MODELING is an interactive application for editing velocity models, and ray-tracing. Synthetic traveltimes computed by the MODELING application can be directly compared with the observed waveforms in the PASTEUP application. This reduces subjectivity in crustal structure modelling because traveltime picking, which is one of the most subjective process in the crustal structure analysis, is not required. MODELING can convert an editable layered structure model into two-way traveltimes which can be compared with time-sections of Multi Channel Seismic (MCS) reflection data. Direct comparison between the structure model of wide-angle data with the reflection data will give the model more credibility. In addition, both PASTEUP and MODELING are efficient tools for handling a large dataset. These software tools help us develop more plausible lithospheric-scale structure models using wide-angle seismic data.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.891-897
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• 2021

With the development of Amyloid PET Tracer, the accuracy of Alzheimer's diagnosis can be improved through the identification of beta-amyloid neurites. However, the long image acquisition time of 20 minutes can be difficult for the patient. PET/CT scans are sensitive to patient movement and may partially affect test results. In this study, we studied the proper image acquisition time without affecting the quantitative evaluation of the image through the list mode acquisition method according to the time of the distribution of radioactive drugs in the body. The list mode includes information about time compared to the existing frame mode, and it is easy to analyze data because it can reconstruct images about the time that researchers want. The research method obtained a reconstructed image by time using a list mode of 5min frame/bed, 10min frame/bed, 15min frame/bed, and 20min frame/bed to compare the difference between signal-to-pons take ratio (SNR) and lesion-to-pons uptake ratio (LPR) and the difference in reading time to obtain an appropriate image. As a result of quantitative analysis, when measuring in list mode, SUVmean values decreased in 6 regions of interest as the image acquisition time increased, but showed the largest difference in 5 min/bed images, followed by 10 min/bed and 15 min/bed. As a result, the difference in SUVmean values decreased. Therefore, it was found that SUVmean values at 15 min/bed did not differ enough to not affect image evaluation. There was no difference in LPR values. As a result of the qualitative analysis, there was no change in the reading findings according to the PET image acquisition time and there was no significant difference in the qualitative analysis score of the image reconstruction according to time. As a result of the study, there is no significant difference between 15 min/bed and 20 min/bed images during the ¹⁸F-flutemetamol PET/CT test, so it can be said that it is clinically useful to reduce the image acquisition time selectively using 15 min/bed via list mode depending on the patient's condition.