• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1299-1310
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• 1992

Recently, digital realizations of timing recovery circuits for digital data transmission are of growing interest. As a result of digital realization of timing recovery circuits, new digital algorithms for timing error detection are required. In this paper, we present a new digital Angular Form(AF) algorithm which can be directly applied to QPSK modulation technique. AF algorithm is basically developed on the concepts of detected angle form and transition logic table. We evaluated the performance of this algorithm by Monte-Carlo simulation method under Gaussian and Impulsive noise environments. From the performance evaluation result, we show that the performance of AF Algorithm is better than that of Gardner in BER, RMS jitter, S-curve.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2547-2554
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• 2009

In this paper, we proposed a face detection algorithm and a hardware implementation method for ROI(Region Of Interest) of AF(Auto Focusing). We used face features in skin regions of YCbCr color space for face detection. The face features are the number of skin pixels in face regions, edge pixels in eye regions, and shadow pixels in lip regions. The each feature was statistically selected by 2,000 sample pictures of face. The proposed algorithm detects two faces that are closer center of the image for considering the effectiveness of hardware resource. The detected faces are displayed by rectangle for ROI of AF, and the rectangles are represented by positions in the image about starting point and ending point of the rectangles. The proposed face detection method was verified by using FPGA boards and mobile phone camera sensor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2655-2663
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• 2011

Several algorithms have been developed to detect AF which rely either on the form of P waves or the based on the time frequency domain analysis of RR variability. However, locating the P wave fiducial point is very difficult because of the low amplitude of the P wave and the corruption by noise. Also, the time frequency domain analysis of RR variability has disadvantage to get the details of irregular RR interval rhythm. In this study, we describe an atrial fibrillation detection algorithm through non-linear analysis of irregular RR interval rhythm based on the variability, randomness and complexity. We employ a new statistical techniques root mean squares of successive differences(RMSSD), turning points ratio(TPR) and sample entropy(SpEn). The detection algorithm was tested using the optimal threshold on two databases, namely the MIT-BIH Atrial Fibrillation Database and the Arrhythmia Database. We have achieved a high sensitivity(Se:94.5%), specificity(Sp:96.2%) and Se(89.8%), Sp(89.62%) respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1047-1054
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• 2012

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its risk increases with age. Conventionally, the way of detecting AF was the time·frequency domain analysis of RR variability. However, the detection of ECG signal is difficult because of the low amplitude of the P wave and the corruption by the noise. Also, the time·frequency domain analysis of RR variability has disadvantage to get the details of irregular RR interval rhythm. In this study, we describe an atrial fibrillation pattern analysis based on symbolization and information entropy. We transformed RR interval data into symbolic sequence through differential partition, analyzed RR interval pattern, quantified the complexity through Shannon entropy and detected atrial fibrillation. The detection algorithm was tested using the threshold between 10ms and 100ms on two databases, namely the MIT-BIH Atrial Fibrillation Database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1131-1143
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• 2016

Differential detection schemes do not require any channel estimation, which can be employed under user mobility with low computational complexity. In this work, a soft-input soft-output (SISO) differential detection algorithm is proposed for amplify-and-forward (AF) over time-varying relaying channels based cooperative communications system. Furthermore, maximum-likelihood (ML) detector for M-ary differential Phase-shift keying (DPSK) is derived to calculate a posteriori probabilities (APP) of information bits. In addition, when the SISO is exploited in conjunction with channel decoding, iterative detection and decoding approach by exchanging extrinsic information with outer code is obtained. Finally, simulation results show that the proposed non-coherent approach improves detection performance significantly. In particular, the system can obtain greater performance gain under fast-fading channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.536-542
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• 2011

For efficient utilization of spectrum resources in TV white space after DTV transition, FCC allowed usage of the spectrum for CR system. The CR system is required to cognize channel usage state for utilizing the unused spectrum in TV white space which coexists various primary and secondary systems. In the meantime, as a demand for high throughput communication had been increased recently, CR systems also consider to adopt channel bonding technology, thus spectrum sensing for channel bonded system is essentially required. In this paper, we propose a novel spectrum sensing algorithm for channel bonding system using a single channel receiver. For IEEE 802.l1af signal, the proposed algorithm provide detection probability of 90% with false alarm probability 10% at SNR -18dB for single channel system and at SNR -7dB for 8 channel bonded system, respectively. Utilizing the proposed scheme, we can detect channel bonded signal using only a single receiver, therefore system overhead for spectrum sensing can be reduced significantly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.959-962
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• 2012

In the process of image acquisition, transmission and storage, image degradation occurs due to various reason, the mainly reason is noise. To restore basic methods used images of impulse noise pollution by SM, AF, CWMF. In this paper, using the modified filter to remove impulse noise. The method consists of detection and noise filtering of the noise signal. For a non-noise signal is intact, the noise signal is filtered according to the algorithm. And then through the simulation is compared with known basic methods, with PSNR as judged by reference.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.233-238
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• 2009

In this paper, we propose the methods to select the stable region for the detect region which is required in the system used the face to the ROI in the auto-focus digital camera. this method regards the face region as the ROI in the progressive input frame and focusing the region in the mobile camera embeded ISP module automatically. The learning algorithm to detect the face is the Adaboost algorithm. we proposed the method to detect the slanted face not participate in the train process and postprocessing method for the results of detection, and then we proposed the stabilization method to sustain the region not shake for the region. we estimated the capability for the stabilization algorithm using the RMS between the trajectory and regression curve.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.15-26
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• 2012

In this paper, we perform interference cancellation in multiuser MIMO (Multiple Input Multiple Output) relay network with improved Amplify-and-Forward (AF) and Decode-and-Forward (DF) relay protocols. The work of interference cancellation is followed by evolved NodeB (eNB), Relay Node (RN) and User Equipment (UE) to improve the error performance of whole transmission system with the explicit use of relay node. In order to perform interference cancellation, we use Dirty Paper Coding (DPC) and Thomilson Harashima Precoding (THP) allied with detection techniques Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Successive Interference Cancellation (SIC) and Ordered Successive Interference Cancellation (OSIC). These basic techniques are studied and improved in the proposal by using the functions of relay node. The performance is improved by Decode-and-Forward which enhance the cancellation of interference in two layers at the cooperative relay node. The interference cancellation using weighted vectors is performed between eNB and RN. In the final results of the research, we conclude that in contrast with the conventional algorithms, the proposed algorithm shows better performance in lower SNR regime. The simulation results show the considerable improvement in the bit error performance by the proposed scheme in the LTE-Advanced system.