• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.543-550
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• 2000

An adaptive bit-reduced mean absolute difference (ABRMAD) is presented as a criterion for the block-matching algorithm (BMA) to reduce the complexity of the VLSI Implementation and to improve the processing time. The ABRMAD uses the lower pixel resolution of the significant bits instead of full resolution pixel values to estimate the motion vector (MV) by examining the pixels Ina block. Simulation results show that the 4-bit ABRMAD has competitive mean square error (MSE)results and a half less hardware complexity than the MAD criterion, It has also better characteristics in terms of both MSE performance and hardware complexity than the Minimax criterion and has better MSE performance than the difference pixel counting(DPC), binary block-matching with edge-map(BBME), and bit-plane matching(BPM) with the same number of bits.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.177-187
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• 2014

This paper proposes a fast subspace tracking methods, which is called GVFF FAPI, based on FAPI (Fast Approximated Power Iteration) method and GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Lease Squares). Since the conventional FAPI uses a constant forgetting factor for estimating covariance matrix of source signals, it has difficulty in applying to non-stationary environments such as continuously changing DOAs of source signals. To overcome the drawback of conventioanl FAPI method, the GVFF FAPI uses the gradient-based variable forgetting factor derived from an improved means square error (MSE) analysis of RLS. In order to achieve the decreased subspace error in non-stationary environments, the GVFF-FAPI algorithm used an improved forgetting factor updating equation that can produce a fast decreasing forgetting factor when the gradient is positive and a slowly increasing forgetting factor when the gradient is negative. Our numerical simulations show that GVFF-FAPI algorithm offers lower subspace error and RMSE (Root Mean Square Error) of tracked DOAs of source signals than conventional FAPI based MUSIC (MUltiple SIgnal Classification).

• Tunnel and Underground Space
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• v.31 no.6
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• pp.508-519
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• 2021

In this study, a model was developed to predict the peak particle velocity (PPV) that affects people and the surrounding environment during blasting. Four machine learning models using the k-nearest neighbors (kNN), classification and regression tree (CART), support vector regression (SVR), and particle swarm optimization (PSO)-SVR algorithms were developed and compared with each other to predict the PPV. Mt. Yogmang located in Changwon-si, Gyeongsangnam-do was selected as a study area, and 1048 blasting data were acquired to train the machine learning models. The blasting data consisted of hole length, burden, spacing, maximum charge per delay, powder factor, number of holes, ratio of emulsion, monitoring distance and PPV. To evaluate the performance of the trained models, the mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) were used. The PSO-SVR model showed superior performance with MAE, MSE and RMSE of 0.0348, 0.0021 and 0.0458, respectively. Finally, a method was proposed to predict the degree of influence on the surrounding environment using the developed machine learning models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.471-478
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• 2013

Powerful error control and increase in the number of bits per symbol should be provided for future high-quality communication systems. Each message bit may have different importance in multimedia data. Hence, UEP(unequal error protection) may be more efficient than EEP(equal error protection) in such cases. And the LDPC(low-density parity-check) code shows near Shannon limit error correcting performance. Therefore, the effect of UEP with LDPC codes is analyzed for high-quality message data in this paper. The relationship among MSE(mean square error), BER(bit error rate) and the number of bits per symbol is analyzed theoretically. Then, total message bits in a symbol are classified into two groups according to importance to prove the relationship by simulation. And the UEP performance is obtained by simulation according to the number of message bits in each group with the constraint of a fixed total code rate and codeword length. As results, the effect of UEP with the LDPC codes is analyzed by MSE according to the number of bits per symbol, the ratio of the message bits, and protection level of the classified groups.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.8
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• pp.584-593
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• 1987

A new combined approximation method using Routh stability array and mean-square error (MSE) method is proposed for deriving reduced-order z-transter functions for discrete time systems. The Routh stability array is used to obtain the reduced-order denominator polynomial, and the numerator polynomial is obtained by minimizing the mean-square error between the unit step responses of the original system and reduced model. The advantages of the new combined approximation method are that the reduced model is always stable provided the original model is stable and the initial and steady-state characteristics of the original model can be preserved in the reduced model.

• Journal of Navigation and Port Research
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• v.36 no.8
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• pp.637-641
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• 2012

In this paper, the method that reduce a computation time by optimizing computation process is proposed to realize low-power underwater acoustic communication system. At first, dependency of decision delay on tap length of linear equalizer was investigated. Variance is calculated based on this result, and the optimal decision delay bound is estimated. In addition to decide optimal tap length with decision delay, we extracted the MSE(Mean Square Error) graph. From the graph, we obtained variance value of the MSE-decision delay, and estimated the optimum decision delay range from the variance value. Also, using the extracted optimal parameters, we performed a simulation. According to the result, the simulation employing optimal tap length, which is only 40% of maximum tap length, showed a satisfactory performance comparable to simulation employing maximum tap length. We verified that the proposed method has 33% lower tap length than maximal tap length via sea trial.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.27-33
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• 2011

In digital communication system that the Modified Constant Modulus Algorithm (MCMA) reduced the use of the adaptive equalization algorithm to combat the Inter-symbol Interference (ISI). MCMA is relatively brief operation. The major point of MCMA that it only achieves moderate convergence rate and steady state mean square error (MSE). In this paper suggest, MCMA equalization improve the performance with parallel structure. It combines Modified Constant Modulus Algorithm(MCMA) and Modified Decision Directed(MDD) algorithm. By exploiting the inherent structural relationship between the 4-QAM signal's coordinates and 16-QAM signal's coordinates, another style of cost function for Modified Constant Modulus Algorithm(MCMA) is defined and If it happen to offset of received signals and MCMA is poor performance in order to overcome this because the paper combines apply for MCMA and MDD(Modified Decision Direct) algorithm. By computer simulation, we confirmed that the proposed PMCMA-MDD algorithm has the fater convergence rate and steady mean square error than the conventional MCMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.232-239
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• 2006

In this paper, we analyze the preamble model for Wireless PAN(WPAN) in proposed Ultra WideBand(UWB) Multi-Band OFDM(MB-OFDM) system of IEEE 802.15.3a standard. Besides, we propose effective Carrier Frequency Offset and Symbol Timing Offset Estimation algorithm which offers enhanced performance, and analyze its performance using Detection Probability, False Alarm Probability, Missing Probability, Mean Acquisition Time and MSE(Mean Square Error) through simulation in AWGN and UWB channel environments.

• ETRI Journal
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• v.33 no.5
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• pp.806-809
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• 2011

This letter considers the channel estimation for two-way relay MIMO OFDM systems. A least square (LS) channel estimation algorithm under block-based training is proposed. The mean square error (MSE) of the LS channel estimate is computed, and the optimal training sequences with respect to this MSE are derived. Some numerical examples are presented to evaluate the performance of the proposed channel estimation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.566-578
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• 2018

In this paper, we design a segment training based individual channel estimation (STICE) scheme for the classical two-way relay network (TWRN) with multi-pair sources (MPS) and amplify-and-forward (AF). We adopt the linear minimum mean square error (LMMSE) channel estimator to minimize the mean square error (MSE) without channel estimation error, where the optimal power allocation strategy from the relay for different sources is obtained. Then the MSE gains are given with different source pairs among the proposed power allocation scheme and the existing power allocation schemes. Numerical results show that the proposed method outperforms the existing ones.