• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.2
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• pp.140-148
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• 2000

A robust current control technique with a simple time delayed estimator for a permanent magnet synchronous m motor (PMSM) drive is presented. Among the various CWTent control schemes for a voltage source inverter-fed P PMSM drive, the predictive control is known to give a superior performance. This control technique, however, r requires the full knowledge of machine parameters and operating conditions, and gives an unsatisfactory r response under the parameter mismatch between the motor and controller. To overcome such a limitation, the d disturbances caused by the parameter valiations will be estimated by using a" time delay contTol approach and u used for the computation of the reference voltages by a simple feedforwal"d control. The proposed control $ scheme is implemented on a PMSM using the software of DSP TlVIS:32OC:30 and the effectiveness is verified d through the comparative simulations and experiments.periments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.685-692
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• 2008

In this paper, we propose a timing recovery loop for Inmarsat mini-m system downlink receiver. Inmarsat mini-m system requires a timing recovery loop which is robust in frequency offset and has fast acquisition because Inmarsat mini-m system specification requires frequency tolerance is required of ${\pm}924$ Hz (signal bandwidth: 2.4 kHz) and acquisition time of UW (Unique Word) signal duration (15ms).Therefore, we propose a timing recovery loop which is suitable for Inmarsat mini-m system. The proposed timing recovery loop adopted noncoherent UW detector and differential ELD which applied differential UW signal for stability and fast acquisition in frequency offset environment. Simulation results show that the proposed timing recovery loop has stable operation and fast acquisition in frequency offset environment for the system.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1247-1259
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• 2005

This paper proposes a real-time face recognition system which detects multiple faces from low resolution video such as web-camera video. Face recognition system consists of the face detection step and the face classification step. At First, it finds face region candidates by using AdaBoost based object detection method which have fast speed and robust performance. It generates reduced feature vector for each face region candidate by using principle component analysis. At Second, Face classification used Principle Component Analysis and multi-SVM. Experimental result shows that the proposed method achieves real-time face detection and face recognition from low resolution video. Additionally, We implement the auto-tracking face recognition system using the Pan-Tilt Web-camera and radio On/Off digital door-lock system with face recognition system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.58-67
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• 2009

A correspondence matching is one of the important tasks in computer vision, and it is not easy to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. A SURF(Speeded Up Robust Features) algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform) with closely maintaining the matching performance. However, because SURF considers only gray image and local geometric information, it is difficult to match corresponding points on the image where similar local patterns are scattered. In order to solve this problem, this paper proposes an extended SURF algorithm that uses the invariant color and global geometric information. The proposed algorithm can improves the matching performance since the color information and global geometric information is used to discriminate similar patterns. In this paper, the superiority of the proposed algorithm is proved by experiments that it is compared with conventional methods on the image where an illumination and a view point are changed and similar patterns exist.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.417-424
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• 2010

In this paper the real-time face region was detected by suggesting the rectangular feature-based classifier and the robust detection algorithm that satisfied the efficiency of computation and detection performance was suggested. By using the detected face region as a recognition input image, in this paper the face recognition method combined with PCA and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input face image, this method computes the eigenface through PCA and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the face recognition is performed by inputting the multi-layer neural network.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.1
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• pp.41-46
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• 2014

In this paper, we propose a novel voice activity detection (VAD) algorithm using feature vectors based on TE (teager energy). Specifically, power spectral deviation (PSD), which is used as the feature for the VAD in the IS-127 noise suppression algorithm, is obtained after the input signal is transfomed by Teager energy operator. In addition, the TE-based likelihhod ratio are derived in each frame to modifiy the PSD for further VAD. The performance of our proposed VAD algorithm are evaluated by objective testing (total error rate, receiver operating characteristics, perceptual evaluation of speech quality) under various environments, and it is found that the proposed method yields better results than conventional VAD algorithms in the non-stationary noise environments under 5 dB SNR (total error rate = 2.6% decrease, PESQ score = 0.053 improvement).

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.21-30
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• 2014

The use of induction motors has been recently increasing in a variety of industrial sites, and they play a significant role. This has motivated that many researchers have studied on developing fault detection and classification systems of induction motors in order to reduce economical damage caused by their faults. To early identify induction motor faults, this paper effectively estimates spectral envelopes of each induction motor fault by utilizing a linear prediction coding (LPC) analysis technique and an expectation maximization (EM) algorithm. Moreover, this paper classifies induction motor faults into their corresponding categories by calculating Mahalanobis distance using the estimated spectral envelopes and finding the minimum distance. Experimental results show that the proposed approach yields higher classification accuracies than the state-of-the-art conventional approach for both noiseless and noisy environments for identifying the induction motor faults.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.316-320
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• 2015

In this paper, the pole filtering concept is applied to the Mel-frequency cepstral coefficient (MFCC) feature vectors in the conventional cepstral mean normalization (CMN) and cepstral mean and variance normalization (CMVN) frameworks. Additionally, performance of the cepstral mean and scale normalization (CMSN), which uses scale normalization instead of variance normalization, is evaluated in speech recognition experiments in noisy environments. Because CMN and CMVN are usually performed on a per-utterance basis, in case of short utterance, they have a problem that reliable estimation of the mean and variance is not guaranteed. However, by applying the pole filtering and scale normalization techniques to the feature normalization process, this problem can be relieved. Experimental results using Aurora 2 database (DB) show that feature normalization method combining the pole-filtering and scale normalization yields the best improvements.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.755-760
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• 2011

This paper presents a method for improving the positioning accuracy of the laser navigation. As a wireless navigation system, the laser navigation which is more flexible than a wired guidance system is used for the localization and control of an AGV(automatic guided vehicle). However, the laser navigation causes the large positioning error while the AGV turns or moves fast. To solve the problem, we propose the method for improving the positioning accuracy of the laser navigation using particle filter which has robust and reliable performance in non-linear/non-gaussian systems. For the experiment, we use the actual fork-type AGV. The AGV has a gyro, two encoders and a laser navigation. To verify the performance, the proposed method is compared with the laser navigation which is a product. In the experimental result, we verified that the proposed method could improve the positioning accuracy by approximately 66.5%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.1
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• pp.235-242
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• 2011

The control performance in active structural control system can be drastically deteriorated when the modeling errors and the uncertainties existing in the disturbances are disregarded in the designing stage. It can even throw the control system into an unstable phase, resulting in out of control against the seismic excitations. The purpose of the study is to investigate the control effectiveness of a non-linear control system called sliding mode controller(SMC) in cooperation with a Tuned Mass Damper subjected to the three seismic excitations selected from the FFT analysis. Even though the transient performance such as settling time and overshoot were deteriorated, the robustness against the system stability was appeared from SMC when the structural masses and stiffness perturbed within the range of ${\pm}30%$. SMC is a feasible technique for active structural control in cooperation with TMD against seismic disturbances, exhibiting robustness in perturbation of system stiffness and mass as well as uncertainties of the disturbances.