• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.42-49
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• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.595-603
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• 2015

With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.319-327
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• 2012

In this paper, we present a sign language recognition model which does not use any wearable devices for object tracking. The system design issues and implementation issues such as data representation, feature extraction and pattern classification methods are discussed. The proposed data representation method for sign language patterns is robust for spatio-temporal variances of feature points. We present a feature extraction technique which can improve the computation speed by reducing the amount of feature data. A neural network model which is capable of incremental learning is described and the behaviors and learning algorithm of the model are introduced. We have defined a measure which reflects the relevance between the feature values and the pattern classes. The measure makes it possible to select more effective features without any degradation of performance. Through the experiments using six types of sign language patterns, the proposed model is evaluated empirically.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.229-232
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• 2012

This paper describes performance evaluation using fixed-point Matlab modeling and simulation, and hardware design of LDPC decoder which is based on Improved Normalized Min-Sum(INMS) decoding algorithm. The designed LDPC decoder supports 19 block lengths(576~2304) and 6 code rates(1/2, 2/3A, 2/3B, 3/4A, 3/4B, 5/6) of IEEE 802.16e mobile WiMAX standard. Considering hardware complexity, it is designed using a block-serial(partially parallel) architecture which is based on layered decoding scheme. A DFU based on sign-magnitude arithmetic is adopted to minimize hardware area. Hardware design is optimized by using INMS decoding algorithm whose performance is better than min-sum algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1346-1353
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• 1999

We propose the MADF(multiplication free adaptive digital filter) algorithm and implement the fractionally spaced equalizer based on it. To evaluate the performance of proposed MADF algorithm, fractionally spaced equalizer(FSE) is used. Especially, we present that this method have the advantages for the condition having the low-frequency and slow speed

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.431-434
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• 2006

현재 사용되는 디지털 신호처리 방식의 GPS(Global Positioning System) 수신기는 최소의 RF 블록만을 이용하여 모든 디지털 신호 처리를 소프트웨어로 수행하고 있다. 소프트웨어 GPS수신기의 장점으로는 디지털 신호처리 과정이 모두 소프트웨어로 구현되어 있기 때문에 새로운 구현 방식이나 알고리즘을 적용할 시, 하드웨어 변경은 필요가 없게 되고, 소프트웨어 재설계만으로 가능하다. GPS 수신기의 Tracking module 성능은 DLL discriminator function과 FLL discriminator function의 Algorithm에 의해서 영향을 받게 된다. DLL discriminator function algorithm에는 dot-product 와 normalized dot-product 방법 등이 있으며, FLL discriminator function algorithm에는 sign(dot)(cross)-product 와 cross-product 그리고 ATAN 방법이 있다. 이러한 discriminator function들은 algorithm에 따라 input error에 대한 discriminator의 출력 값을 일정한 범위에서의 차이를 나타내게 되면서 ranging accuracy에서 차이가 나타나게 된다. 본 논문에서는 Nordnav 소프트웨어 GPS 수신기를 이용하여 DLL discriminator algorithm과 FLL discriminator algorithm의 성능을 비교, 분석을 하고 Tracking accuracy, sensibility, 그리고 multipath rejection에 대해서 알아보고자 한다.

• Journal of Industrial Technology
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• v.9
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• pp.127-131
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• 1989

순허수 고유치를 포함하고 있는 행렬이 행렬부호함수 알고리즘에서 보이는 성질을 규명했다. 역행렬이 존재하는 행렬도 이 알고리즘에서는 행렬의 조건과 무관하게 특이행렬이 될 수 있음을 보였다. 이 특성을 이용해서 이론적으로 모든 고유치를 알아낼 수 있다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.418-426
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• 2019

Recently, many studies on vital sign detection using a radar sensor related to Internet of Things(IoT) smart home systems have been conducted. Because vital signs such as respiration and cardiac rates generally cause micro-motions in the chest or back, the phase of the received echo signal from a target fluctuates according to the micro-motion. Therefore, vital signs are usually detected via spectral analysis of the phase. However, the probability of false alarms in cardiac rate detection increases as a result of various problems in the measurement environment, such as very weak phase fluctuations caused by the cardiac rate. Therefore, this study analyzes the difficulties of vital sign detection and proposes an efficient vital sign detection algorithm consisting of four main stages: 1) phase decomposition, 2) phase differentiation and filtering, 3) vital sign detection, and 4) reduction of the probability of false alarm. Experimental results using impulse-radio ultra-wideband radar show that the proposed algorithm is very efficient in terms of computation and accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1071-1076
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• 2006

In this paper, we develop face and hand tracking for sign language recognition system. The system is divided into two stages; the initial and tracking stages. In initial stage, we use the skin feature to localize face and hands of signer. The ellipse model on CbCr space is constructed and used to detect skin color. After the skin regions have been segmented, face and hand blobs are defined by using size and facial feature with the assumption that the movement of face is less than that of hands in this signing scenario. In tracking stage, the motion estimation is applied only hand blobs, in which first and second derivative are used to compute the position of prediction of hands. We observed that there are errors in the value of tracking position between two consecutive frames in which velocity has changed abruptly. To improve the tracking performance, our proposed algorithm compensates the error of tracking position by using adaptive search area to re-compute the hand blobs. The experimental results indicate that our proposed method is able to decrease the prediction error up to 96.87% with negligible increase in computational complexity of up to 4%.

• Smart Structures and Systems
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• v.16 no.1
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• pp.223-242
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• 2015

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.