• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.518-522
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• 2002

This paper proposes a new application of Fuzzy logic to Variable Step Size Least Mean Square (VS-LMS) adaptive beamforming algorithm in CDMA systems. The proposed algorithm adjusts the step size of the Least Mean Square (LMS) by using the application of Fuzzy logic in which the increase or decrease of step size depends on the fuzzy inference results of the Mean Square Error (MSE). Computer simulation results show that the proposed algorithm has a better capacity of tracking compared with the conventional LMS algorithms and other variable step size LMS algorithms.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.135-141
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• 2014

The inherent feature of the highly efficient spectrum usage has made Orthogonal Frequency Division Multiplexing (OFDM) preferable for Communication Standards. This study evaluated the performance of a Least Square (LS) estimator for a comb-type pilot insertion scheme over a fast fading Rayleigh channel. A High Peak-to-Average Power Ratio (PAPR) is one of the major downsides of the OFDM. The effects of an increase in the number of subcarriers on PAPR and the performance of the LS Estimator were studied. Increasing the number of subcarriers while keeping the pilots overhead constant resulted in improved performance of the LS estimator but the PAPR increased with increasing number of subcarriers. Therefore some trade-off between the number of subcarriers and the performance of the OFDM system is needed. The Mean Square Error (MSE) expression was also derived for the LS estimator in the case of a comb-type pilot arrangement. The MSE expression clearly explains the effects of the number of subcarriers on the performance of the LS estimator.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.661-668
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• 2006

There have been some controversies on the use of the coefficient of determination for linear no-intercept model. One definition of the coefficient of determination, $R^2={\sum}\;{\widehat{y^2}}\;/\;{\sum}\;y^2$, is being widely accepted only for linear no-intercept models though Kvalseth (1985) demonstrated some possible pitfalls in using such $R^2$. Main objective of this note is to report that $R^2$ is not a desirable measure of fit for the no-intercept linear model. In fact it is found that mean square error(MSE) could replace $R^2$ efficiently in most cases where selection of no-intercept model is at issue.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1271-1277
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• 2012

In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.509-513
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• 2002

This paper presents a semi-blind Minimum Mean Square Error (MMSE) beamforming adaptive algorithm used far OFDM/CDMA combined system. The proposed algorithm exploits the transmitting pilot signal in the initial period of the transmission to update the weight vector. Then it applies the blind adaptive period to update the weight vector, in which the pilot signal is no longer used. The derivation of the algorithm based on the Mean Square Error (MSE) criterion is also presented. Computer simulation is carried out to verify the performance of the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8A
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• pp.813-819
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• 2007

In this paper, the effect of a propagation delay resulting from the use of an OFDM-based cellular system with a transparent mobile multi-hop relay(MMR) is initially analyzed. Then, channel estimation techniques, a least square(LS) method and a minimum mean square error(MMSE) method, for the OFDM systems with throughput enhancement(TE) MMR or cooperative MMR are proposed. The proposed channel estimation techniques can overcome the performance degradation caused by the propagation delay in TE MMR or cooperative MMR systems. It is demonstrated by computer simulation that the proposed channel estimation techniques for OFDM systems with transparent MMR are superior to the conventional techniques in terms of mean square error(MSE) and bit error rate(BER).

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.987-994
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• 2020

In this paper, we studied the effect of kernel size of CNN layer on performance in acoustic noise attenuators. This system uses a deep learning algorithm using a neural network adaptive prediction filter instead of using the existing adaptive filter. Speech is estimated from a single input speech signal containing noise using a 100-neuron, 16-filter CNN filter and an error back propagation algorithm. This is to use the quasi-periodic property in the voiced sound section of the voice signal. In this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed to verify the performance of the noise attenuator for the kernel size. As a result of the simulation, when the kernel size is about 16, the MSE and MAE values are the smallest, and when the size is smaller or larger than 16, the MSE and MAE values increase. It can be seen that in the case of an speech signal, the features can be best captured when the kernel size is about 16.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.641-648
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• 2011

Frequency domain equalization is the most promising technology that has relatively low complexity in multipath channel. A frame of single carrier system with frequency domain equalization (SC-FDE) has cyclic prefix to mitigate effect of delay spread. After synchronization and equalization procedure on the SC-FDE system, common phase offset (CPO) that can introduce performance degradation caused by phase mismatch between transmitter and receiver oscillators is remained. In this paper, common phase offset tracking in frequency domain is proposed. To track CPO, constant amplitude zero autocorrelation code sequence as training sequence is adopted. By using numerical results, performance of mean square error is evaluated. The results show that MSE of CPO has similar performance compare to the time-domain estimation and there is no need of domain conversion.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.379-386
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• 2005

This paper provides a rigorous theory for analysis of quantization effects and optimum filter bank design in quantized multidimensional subband filter banks. Even though subband filter design has been a hot topic for last decades, a few results have been reported on the subband filter with a quantizer. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. Using polyphase decomposition of the analysis/synthesis filter banks, we derive the exact expression for the output mean square quantization error. Based on the minimization of the output mean square error, the technique for optimal filter design methodology is developed. Numerical design examples for optimum nonseparable paraunitary and biorthogonal filter banks are presented with a quincunx subsampling lattice. Through the simulation, $10\~20\;\%$ decreases in MSE have been observed compared with subband filter with no quantizers especially for low bit rate cases.

• ETRI Journal
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• v.38 no.3
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• pp.435-443
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• 2016

In this paper, an efficient beam tracking algorithm for a regularized zero-forcing (RZF) approach in slowly fading multiple-input and single-output (MISO) broadcast channels is considered. By modifying an RZF equation, an RZF beam tracking algorithm is proposed using matrix perturbation theory. The proposed algorithm utilizes both beams from the previous time step and channel difference (between the previous and current time steps) to calculate the RZF beams. The tracking performance of the proposed algorithm is analyzed in terms of the mean square error (MSE) between a tracking approach and an exact recomputing approach, and in terms of the additional MSE caused by the beam tracking error at the receiver. Numerical results show that the proposed algorithm has almost the same performance as the exact recomputing approach in terms of the sum rate.