• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.63-74
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• 2023

High-reliability prediction of dam inflow is necessary for efficient dam operation. Recently, studies were conducted to predict the inflow of dams using Multi Layer Perceptron (MLP). Existing studies used the Gradient Descent (GD)-based optimizer as the optimizer among MLP operators to find the optimal correlation between data. However, the GD-based optimizers have disadvantages in that the prediction performance is deteriorated due to the possibility of convergence to the local optimal value and the absence of storage space. This study improved the shortcomings of the GD-based optimizer by developing Adaptive moments combined with Improved Harmony Search (AdamIHS), which combines Adaptive moments among GD-based optimizers and Improved Harmony Search (IHS). In order to evaluate the learning and prediction performance of MLP using AdamIHS, Daecheong Dam inflow was learned and predicted and compared with the learning and prediction performance of MLP using GD-based optimizer. Comparing the learning results, the Mean Squared Error (MSE) of MLP, which is 5 hidden layers using AdamIHS, was the lowest at 11,577. Comparing the prediction results, the average MSE of MLP, which is one hidden layer using AdamIHS, was the lowest at 413,262. Using AdamIHS developed in this study, it will be possible to show improved prediction performance in various fields.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.29-31
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• 2013

본 논문에서는 기존라디오(primary) 네트워크와 스펙트럼을 공유하는(spectrum sharing) 인지라디오(cognitive radio) 네트워크에서 비재생적(non-regenerative) 다중안테나 중계 (relay) 시스템을 위한 소스(source) 및 중계기 프리코딩(precoding) 기법을 제안한다. 제안된 기법은 소스와 중계기 프리코딩 행렬의 최적해를 구하기 위해 QCQP(Quadratically Constrained Quadratic Programming) 문제를 통해 구한다. 제안된 기법은 기존라디오 수신기에서의 간섭세기 제한을 만족하면서 낮은 MSE(Mean squared error)와 높은 MI(Mutual Information)를 달성함을 모의실험결과를 통해 보인다. 또한 아주 빠른 속도로 최적해로 수렴함을 보이고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.3
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• pp.193-203
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• 1988

In this paper, an echo canceller(EC) using decision feedback at the ISDN U-interface is presented and its performance based on the stochastic iteration algorithm is analyzed, and compared with the other conventional EC. The steady state mean-squared error(MSE) by the analytical resutls on the decision feedback-EC turns out to be smaller than that of the other linear EC. The performance of the ECs with the same convergence factor are almost the same regardless of different channel characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.782-787
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• 2007

This paper presents the D(Diagonal)-QR-RLS algorithm which normalizes the fast algorithm minimizes the MSE by using Givens rotated inputs and analyzes its characteristic. This proposed one has computational complexity of O(N) and the merit that it obtains the coefficients of TDL filter directly. Although this proposed normalized algorithm has the similar form to NLMS algorithm, we can see that D-QR-RLS has superior convergence characteristic to NLMS by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2C
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• pp.150-159
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• 2002

This paper presents the convergence time, SER(Symbol Error Rate), MSE(Mean Square Error), hardware complexity and step-size(${\mu}$) about various LMS(Least Mean Square) algorithms in FS-DFE(Fractionally Spaced-Decision Feedback Equalize) for Cable Modem based on MCNS(Multimedia Cable Network System) DOCSIS(Data Over Cable Service Interface Specification) v1.0/v1.1 standards. We designed and simulated using ${SPW}^{TM}$ and synthesized using STD90 library through ${SYNOPSYS}^{TM}$. And also, we adopted the time-multiplexed multiplication and tap shared architecture in order to achieve the low hardware complexity. Simulation results show that DS-LMS algorithms[1][3] is the optimum solution about performace and hardware size. in high order QAM applications. Finally, we achieved area saving about 58% using DS-LMS algorithm compare with conventional equalizer architecture.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.1-8
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• 2010

This paper presentsthe performance study of blind equalizer algorithms for impulsive-noise environments based on Gaussian kernel and constant modulus error(CME). Constant modulus algorithm(CMA) based on CME and mean squared error(MSE) criterion fails in impulsive noise environment. Correntropy blind method recently introduced for impulsive-noise resistance has shown in PAM system not very satisfying results. It is revealed in theoretical and simulation analysis that the maximization of zero-error probability based on CME(MZEP-CME) originally proposed for Gaussian noise environments produces superior performance in impulsive noise channels as well. Gaussian kernel of MZEP-CME has a strong effect of becoming insensitive to the large differences between the power of impulse-infected outputs and the constant modulus value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.529-536
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• 2003

In this Paper, a new DCT HLMS DFE(Discrete Cosine Transform Hierarchical Least Mean Square Decision Feedback Equalizer) algorithm is proposed to improve the convergence speed and MSE(Mean Square Error) performance of a receive channel equalizer in ATSC(Advanced Television System Committee) 8VSB(Vestigial Side Band) digital terrestrial TV system. The proposed algorithm reduces the eigenvalue range of input data autocorrelation by transforming LMS (Least Mean Square) DFE into the subfilter of hierarchical structure. Moreover, the use of DCT and power estimation algorithm makes it possible to reduce the eigenvalue deviation of input data which results from distortion and delay of the receive signal in the miulti-path environment. Simulation results show that proposed DCT HLMS DFE has SNR improvement of approximately 3.8dB, 5dB and 2dB as compared to LMS DFE when the equalized symbol error rate is 0.2 in ATTC defined digital terrestrial TV broadcasting channels A, B and F, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.103-108
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• 2020

This paper related with the performance evaluation of mDSE-MMA adaptive equalization algorithm which is possible to reduce the distortion that occurs in nonlinear communication channel like as additive noise, intersymbol interference and fading when transmitting the QAM signal. The DSE-MMA algorithm is possible to reduce the computational load compared to the presently MMA algorithm, it has the degraded equalization performance by this. In order to improve the performance degradation of DSE-MMA, the mDSE-MMA controls the step size according to the existence of arbitrary radius circle of equalizer output is centered at transmitted symbol point. The performance of proposed mDSE-MMA algorithm were compared to present DSE-MMA using the same channel and noise environment by computer simulation. For this, the recoverd signal constellation which is the output of equalizer, residual isi and MD, MSE learning curve which is represents the convergence performance and SER were applied as performance index. As a result of simulation, the mDSE-MMA has more superior to the DSE-MMA in every performance index.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1471-1479
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• 1999

This paper presents an adaptive beamforming algorithm for an MC-CDMA system with an adaptive array antenna. By employing an antenna array at the receiver of an MC-CDMA system, the performance of an MC-CDMA system, which is known to be effective for high data rate transmission due to its robustness to multipath fading and its simplicity for using a simple one-tap equalizer, is shown to be significantly improved. The proposed algorithm for adaptive beanforming in an MC-CDMA system is derived by (1) calculating the error signals between the pilot symbols of desired user and the received pilot signals in frequency domain, (2) transforming the frequency-domain error signals into time-domain error signals, (3) updating the filter coefficients of the adaptive beamformer in the direction of minimizing the MSE. Convergence behavior and performance improvement of the proposed approach are demonstrated through computer simulation by applying it to the conventional MC-CDMA system.