• Journal of the Institute of Convergence Signal Processing
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• v.21 no.2
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• pp.55-60
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• 2020

In this paper, we propose a fast block matching algorithm of motion estimation using early detection of optimal candidate with high priority and a threshold. Even though so many fast algorithms for motion estimation have been published to reduce computational reduction full search algorithm, still so many works to improve performance of motion estimation are being reported. The proposed algorithm calculates block matching error for each candidate with high priority from previous partial matching error. The proposed algorithm can be applied additionally to most of conventional fast block matching algorithms for more speed up. By doing that, we can find the minimum error point early and get speed up by reducing unnecessary computations of impossible candidates. The proposed algorithm uses smaller computation than conventional fast full search algorithms with the same prediction quality as the full search algorithm. Experimental results shows that the proposed algorithm reduces 30~70% compared with the computation of the PDE and full search algorithms without any degradation of prediction quality and further reduces it with other fast lossy algorithms.

• International Journal of Contents
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• v.8 no.2
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• pp.7-12
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• 2012

Imbalanced data sets are difficult to be classified since most classifiers are developed based on the assumption that class distributions are well-balanced. In order to improve the error back-propagation algorithm for the classification of imbalanced data sets, a new error function is proposed. The error function controls weight-updating with regards to the classes in which the training samples are. This has the effect that samples in the minority class have a greater chance to be classified but samples in the majority class have a less chance to be classified. The proposed method is compared with the two-phase, threshold-moving, and target node methods through simulations in a mammography data set and the proposed method attains the best results.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.697-702
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• 2001

The ring laser gyro(RLG) has been used extensively in strapdown inertial navigation system(SDINS) because of the apparent of having wide dynamic range, digital output and high accuracy. The dithered RLG system has dynamic motion at sensor level, caused by the dithering motion to overcome the lock-in threshold. In this case, an attitude error is produced by not only the true coning of the vehicle motion but also the pseudo coning of the sensor motion. This paper describes the definition of the multi-frequency coning motion and its noncommutativity error to reject the pseudo coning error produced by the sensor motion such as the dithered RLG. The simulation results are presented to minimize the multi-frequency coning error.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.1
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• pp.25-35
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• 2018

This paper describes the measurement of pulse positioning (input time) to calculate a time of arrival (TOA) that takes from transmitting a signal from the target of multilateration (MLAT) system to receiving the signal at the receiver. In this regard, this paper analyzes performances of simple threshold method and level adjust system (LAS) method, which is one of the adaptive threshold detector (ATD) methods, among many methods to calculate pulse positioning of signal received at the receiver. To this end, Cramer-rao lower bound (CRLB) with regard to pulse positioning, which was measured when signals transmitted from a transponder mounted at the target were received at the receiver, was induced and then deviation sizes with regard to pulse positioning, which was measured with simple threshold and LAS methods through MATLAB simulations, were compared. Next, problems occurring according to a difference in amplitude of signals inputted to each receiver are described when pulse positioning is measured at multiple receivers located at a different distance from the target as is the case in the MLAT system. Furthermore, LAS method to resolve the problems is explained. Lastly, this study analyzes whether a pulse positioning error occurring due to the signal noise satisfies the requirement (6 nsec. or lower) recommended for the MLAT system when using these two methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.809-814
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• 2012

We propose an adaptive threshold detector algorithm for multi-level holographic data storage based on the expectation-maximization (EM) method. In this paper, the signal intensities that are passed through the four-level holographic channel are modeled as a four Gaussian mixture with unknown DC offsets and the threshold levels are estimated based on the maximum likelihood criterion. We compare the bit error rate (BER) performance of the proposed algorithm with the non-adaptive threshold detection algorithm for various levels of DC offset and misalignments. Our proposed algorithm shows consistently acceptable performance when the DC offset variance is fixed or the misalignments are lower than 20%. When the DC offset varies with each page, the BER of the proposed method is acceptable when the misalignments are lower than 10% and DC offset variance is 0.001.

• Journal of the Optical Society of Korea
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• v.13 no.3
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• pp.361-366
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• 2009

We propose the performance enhancing method optimization of an asynchronous 2.5 Gbps/1.25 Gbps optical subscriber network with inverse RZ (Return to Zero) coded downstream and NRZ (Non Return to Zero) upstream re-modulation by adjusting threshold level control of a receiver. We theoretically analyze the BER (Bit Error Rate) performance by modeling the occurrence of BER by simulation with MATLAB according to the types of downstream data. The results have shown that the normalized threshold level in an optical receiver could be saturated at 1/3 as the SNR (Signal to Noise Ratio) increases. The needed SNR for obtaining the BER $10^{-9}$ can be reduced by $\sim$5 dB by optimizing the normalized threshold level at 1/3 instead of by using the conventional receiver with threshold level of 0.5. The proposed system can be a useful technology for asynchronous optical access networks with asymmetric upstream and downstream data rates, because the improved minimum receiving power could replace a light source with a source with lower power and lower cost in an OLT (Optical Line Termination).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1660-1668
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• 2004

This paper proposes a Voice Activity Detection (VAD) algorithm based on Radial Basis Function (RBF) network using dual threshold. The k-means clustering and Least Mean Square (LMS) algorithm are used to upade the RBF network to the underlying speech condition. The inputs for RBF are the three parameters in a Code Exited Linear Prediction (CELP) coder, which works stably under various background noise levels. Dual hangover threshold applies in BRF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental result show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.61-66
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• 2005

In this paper, we analyzed the error rate Performance of Convolution coded 16 QAM signal with Optimum Threshold Detection in Rician Fading Enviroments. The performance of 16-QAM signal with CTD (conventional threshold detection) which employs convolution coding technique was analyzed and the performance improvement of convolution coded 16-QAM signal with OTD (optimum threshold detection) which is varied according to fading parameter 'K' and AWGN in Rician Fading channel was simulated. As a result of analysis, it was shown the effect of performance improvement to overcome the environment of mobile radio data communication channel.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.257-264
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• 2013

In this study, we have designed the variable amplitude threshold algorithm that can enhance the accuracy of step count using variable amplitude. This algorithm converts the x, y, z sensor values into a single energy value($E_t$) by using SVM(Signal Vector Magnitude) algorithm and can pick step count out over 99% of accuracy through the peak data detection algorithm and fixed peak threshold. To prove the results, We made the noise filtering with the fixed amplitude threshold from the amplitude of energy value that found out the detection error was increasing, and it's the key idea of the variable amplitude threshold that can be adapted on the continuous data evaluation. The experiment results shows that the variable amplitude threshold algorithm can improve the average step count accuracy up to 98.9% at 10 Hz sampling rate and 99.6% at 20Hz sampling rate.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.619-630
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• 2011

In order to estimate an appropriate threshold and evaluate its performance for the data mixed with two different distributions, nine kinds of well-known classification accuracy measures such as MVD, Youden's index, the closest-to- (0,1) criterion, the amended closest-to- (0,1) criterion, SSS, symmetry point, accuracy area, TA, TR are clustered into five categories on the basis of their characters. In credit evaluation study, it is assumed that the score random variable follows normal mixture distributions of the default and non-default states. For various normal mixtures, optimal cut-off points for classification measures belong to each category are obtained and type I and II error rates corresponding to these cut-off points are calculated. Then we explore the cases when these error rates are minimized. If normal mixtures might be estimated for these kinds of real data, we could make use of results of this study to select the best classification accuracy measure which has the minimum error rate.