• Journal of Environmental Impact Assessment
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• v.29 no.4
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• pp.272-285
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• 2020

We investigated statistical evaluation parameters for 3D meteorological and air quality models and selected several quantitative indicator references, and summarized the reference values of the statistical parameters for domestic air quality modeling researcher. The finally selected 9 statistical parameters are MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias), and the associated reference values are summarized. The results showed that MB and ME have been widely used in evaluating the meteorological model output, and NMB and NME are most frequently used for air quality model results. In addition, discussed are the presentation diagrams such as Soccer Plot, Taylor diagram, and Q-Q (Quantile-Quantile) diagram. The current results from our study is expected to be effectively used as the statistical evaluation parameters suitable for situation in Korea considering various characteristics such as including the mountainous surface areas.

• Investigative Magnetic Resonance Imaging
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• v.19 no.1
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• pp.19-30
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• 2015

Purpose: A new compressed sensing technique by iterative truncation of small transformed coefficients (ITSC) is proposed for fast cardiac CINE MRI. Materials and Methods: The proposed reconstruction is composed of two processes: truncation of the small transformed coefficients in the r-f domain, and restoration of the measured data in the k-t domain. The two processes are sequentially applied iteratively until the reconstructed images converge, with the assumption that the cardiac CINE images are inherently sparse in the r-f domain. A novel sampling strategy to reduce the normalized mean square error of the reconstructed images is proposed. Results: The technique shows the least normalized mean square error among the four methods under comparison (zero filling, view sharing, k-t FOCUSS, and ITSC). Application of ITSC for multi-slice cardiac CINE imaging was tested with the number of slices of 2 to 8 in a single breath-hold, to demonstrate the clinical usefulness of the technique. Conclusion: Reconstructed images with the compression factors of 3-4 appear very close to the images without compression. Furthermore the proposed algorithm is computationally efficient and is stable without using matrix inversion during the reconstruction.

• ETRI Journal
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• v.26 no.5
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• pp.432-436
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• 2004

In this paper, we propose the modified uniformly most powerful (UMP) belief-propagation (BP)-based decoding algorithm which utilizes multiplicative and additive factors to diminish the errors introduced by the approximation of the soft values given by a previously proposed UMP BP-based algorithm. This modified UMP BP-based algorithm shows better performance than that of the normalized UMP BP-based algorithm, i.e., it has an error performance closer to BP than that of the normalized UMP BP-based algorithm on the additive white Gaussian noise channel for low density parity check codes. Also, this algorithm has the same complexity in its implementation as the normalized UMP BP-based algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1203-1210
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• 1999

Coefficients of the adaptive filter are misadjusted by primary signals which are uncorrelated with reference signals of the adaptive filter. In this paper, the normalized sign algorithm is analyzed and compared with the NLMS algorithm by the steady state performance and the transient characteristics when target signals are included in primary signals. The excess mean square error of the NLMS algorithm is proportional to the power of target signals. That of normalized sign algorithm is proportional to the square root of the target signal power. However, the convergence speed of the normalized sign algorithm is slower than that of NLMS algorithm. In this paper, it is shown that theoretical analysis of the steady state performance and the transient characteristics are well consisted with the results of computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.7B
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• pp.937-943
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• 2001

fast fading 채널 특성을 갖는 DS-CDMA 다중 사용자 환경에서 Normalized CMA(Constant Modulus Algorithm)와 Newton 방식을 이용한 CMA를 이용하여 빠른 수렴속도와 작은 평균 자승 오차(Mean Square Error)를 동시에 개선할 수 있는 등화 방법을 제안하였다. Normalized CMA는 Newton 방식을 이용한 CMA에 비해 작은 평균 자승오차를 갖지만 수렴속도가 느리다는 단점이 있다. 반면 Newton 방식을 이용한 CMA는 Normalized CMA에 비해 수렴속도는 빠르지만 큰 평균 자승 오차를 갖는다는 단점이 있다. 따라서 빠른 수렴 속도와 작은 평균 자승 오차를 동시에 얻기 위한 구조를 제안하였으며, 이 구조는 각각의 알고리즘을 사용하는 방법과는 달리 두 개의 알고리즘을 동시에 이용한다. 모의 실험 결과, 제안한 기법이 Normalized CMA보다 약 320번, Newton 방식을 이용한 CMA보다는 170번 정도 빠른 수렴 속도를 나타냈으며, 동시에 수렴시의 평균 자승 오차는 Newton 방식을 이용한 CMA보다 약 0.6dB, Normalized CMA보다 약 0.4dB 정도 낮은 수치를 나타내는 것을 확인할 수 있었다.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.273-279
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• 2012

In this paper, we propose an iterative interstream interference cancellation technique for system with frequency selective multiple-input multiple-output (MIMO) channel. Our method is inspired by the fact that the cancellation of the interstream interference can be regarded as a reduction in the magnitude of the interfering channel. We show that, as iteration goes on, the channel experienced by the equalizer gets close to the single input multiple output (SIMO) channel and, therefore, the proposed SIMO-like equalizer achieves improved equalization performance in terms of normalized mean square error. From simulations on downlink communications of $2{\times}2$ MIMO systems in high speed packet access universal mobile telecommunications system standard, we show that the proposed method provides substantial performance gain over the conventional receiver algorithms.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.89-95
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• 2006

The performance of blind source separation(BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. A post-processing method proposed in this paper was designed to remove the residual component precisely. The proposed method used modified NLMS(normalized least mean square) filter in frequency domain, to estimate cross-talk path that causes residual cross-talk components. Residual cross-talk components in one channel is correspond to direct components in another channel. Therefore, we can estimate cross-talk path using another channel input signals from adaptive filter. Step size is normalized by input signal power in conventional NLMS filter, but it is normalized by sum of input signal power and error signal power in modified NLMS filter. By using this method, we can prevent misadjustment of filter weights. The estimated residual cross-talk components are subtracted by non-stationary spectral subtraction. The computer simulation results using speech signals show that the proposed method improves the noise reduction ratio(NRR) by approximately 3dB on conventional FDICA.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1475-1478
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• 2002

This paper presents a performance analysis of an improved adaptive algorithm proposed by the authors recently. It is based on the normalized least mean square (NLMS) algorithm, which Is one of the major techniques to adapt the cofficients of a transversal filter. Generally, the performance of an adaptive algorithm is often discussed by investigating the mis-adjustment. In this paper, unlike these approaches, a novel analytical method is considered. letting the parameters so that the residual mean square error (MSE) after the convergence of the algorithm is equal to that of the NLMS algorithm, the MSE level is compared. It is shown that the theoretical analysis is agreed with the simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1274-1285
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• 1991

This paper presents a statistical convergence analysis of the normalized least mean square(NLMS)algorithm that employs a single-pole lowpass filter, In this algorithm the lowpass filter is used to adjust its output towards the estimated value of the input signal power recursively. The estimated input signal power so obtained at each time is then used to normalize the convergence parameter. Under the assumption that the primary and reference inputs to the adaptive filter are zero mean wide sense stationary, and Gaussian random processes, and further making use of the independence assumption. we derive expressions that characterize the mean and maen squared behavior of the filter coefficients as well as the mean squared estimation error. Conditions for the mean and mean squared convergence are explored. Comparisons are also made between the performance of the NLMS algorithm and that of the popular least mean square(LMS) algorithm Finally, experimental results that show very good agreement between the analytical and emprincal results are presented.