• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1714-1725
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• 1993

This paper analyzes the properties of such algorithm that corresponds to the nonlinear adaptive algorithm with additional update terms, parameterized by the scalar factors a1, a2, a3 and Presents its structure. The analysis of convergence leads to eigenvalues of the transition matrix for the mean weight vector. Regions in which the algorithm becomes stable are demonstrated. The time constant is derived and the computational complexities of MLMS algorithms are compared with those of the conventional LMS, sign, LFG, and QFG algorithms. The properties of convergence in the mean square are analyzed and the expressions of the mean square recursion and the excess mean square error are derived. The necessary condition for the CFG algorithm to be stable is attained. In the computer simulation applied to the system identification the CFG algorithm has the more computation complexities but the faster convergence speed than LMS, LFG and QFG algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.756-763
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• 2009

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

• Ocean and Polar Research
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• v.25 no.1
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• pp.63-74
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• 2003

The build-up of the heat field in shallow coastal water due to a point source has been investigated using an analytical solution of a time-integral form derived by extending the solutions by Holley(1969) and also presented in Harleman (1971). The uniform water depth is assumed with non-isotropic turbulent dispersion. The alongshore-flow is assumed to be uni-directional, spatially uniform and oscillatory. Due to the presence of the oscillatory alongshore-flow, the heat build-up occurs in an oscillatory manner, and the excess temperature thereby fluctuates in that course and even in the quasi-steady state. A series of calculations reveal that proper choices of the decay coefficient as well as dispersion coefficients are critical to the reliable prediction of the excess temperature field. The dispersion coefficients determine the absolute values of the excess temperature and characterize the shoreline profile, particularly within the tidal excursion distance, while the decay coefficient determines the absolute value of the excess temperature and the convergence rate to that of the quasi-steady state. Within the e-folding time scale $1/k_d$ (where $k_d$ is the heat decay coefficient), heat build-up occurs more than 90% of the quasi-steady state values in a region within a tidal excursion distance (L), while occurs increasingly less the farther we go to the downstream direction (about 80% at 1.25L, and 70% at 1.5L). Calculations with onshore and offshore discharges indicate that thermal spreading in the direction of the shoreline is reduced as the shoreline constraint which controls the lateral mixing is reduced. The importance of collecting long-term records of in situ meteorological conditions and clarifying the definition of the heat loss coefficient is addressed. Interactive use of analytical and numerical modeling is recommended as a desirable way to obtain a reliable estimate of the far-field excess temperature along with extensive field measurements.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.103-111
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• 2011

This study parent-children relationship with the youth of the Internet was to evaluate the impact on. Internet excess utility of adolescents was to influence the, and how we received its relation the influence. This study distinguished their patent-children relation according to the violence and non-interference level and Internet excess utility contains an everyday life problem, we can not do the work to plan, the excess Internet usage, and the complications of the another person. This distinguished with genernal, potent risk, high risk category. The result was as follows: First, potent risk and high risk category appeared in the parent-children relation to be the no- interference. This means that parent-children relation has an influence on internet excess utility of adolescent. Second, the role of parents is important to reduce internet utility of adolescent, and it must understand so that the development stage is careful. We need the supply for adolescent with play and experience program development which can enjoy the leisure culture. We need internet poisoning expert training and the treatment must be achieved with the counselling to be continuous to problem adolescents.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.95-98
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• 2013

The LMS(Least Mean Square) algorithm, one of the most famous, is generally used because of tenacity and high mating spots and simplicity of realization, But it has trade-off between nonuniform collection and EMSE(Excess mean square error). To overcome this weakness, a variable step size is used widely, but it needs a lot of calculation loads. In this paper, we suggest changed algorithm in case of environment changes of cars and reduce amount of calculation as it uses original signal and noise signal of IGC(Instantaneous Gain Control) algorithm. In this paper, logarithmic function is removed because of real-time processing IGC. The performance of proposed algorithm is tested to adaptive noise canceller in automobile.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.28-38
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• 1997

Previously, we have proposed the M-BECM(Modified-Band Edge Component Maximization), which is a symbol synchronization algorithm based on spectral line method for all-digital high speed digital communications. However, Until now, the characteristics of the timing detector based on the spectral line method including M-BECM was not analyzed, particularly the effect of a timing offset at the optimal convergence pont. In this paper, we analyze the timing dtector's characteristics of the M-BECM and present optimal design value. First, the expression for the timing detector's mean value(often called its S-Curver) as a function of the normalized symbol timing offset is derived. Next, the P $D_{bias}$, the value for compensating the timing offset at an optimal convergence point, and the bandwidth of bandpass filter in the timing detector are calculated. It is also shown and analyzed that the P $D_{bias}$ is affected by varuous factors such as the excess bandwidth of input signal, frequency offsets, noise and particularly, the excess bandwidth of input signal is a major parameter to decide P $D_{bias}$. Finally, analytic resutls are compared to simulation results.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.237-247
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• 2016

This study analyzed quantitative effects of ISMS certification. To measure the company value change the stock data was used and the methodology of event study was also applied. Event study methodology is a method of analyzing the effects of information or public announcement about certain events on the stock market through abnormal return of stock price. First, ISMS certification was acquired followed by the measurement of abnormal excess return of company. Based on the increase or decrease of abnormal excess return, the group was classified. There are 3 types of groups("Increase", "Reduce", "Maintain"). Next, the cluster analysis was performed for each group. Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups(clusters). The purpose of this study is to have a quantitative measurement of performance of ISMS certification. So, the result of this study will be promoted a company's ISMS certification acquisition. And it would further be beneficial to your company's information security activities.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.81-88
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• 2021

Convertible bonds are financial products that contain the nature of both bonds and shares, which are generally issued by companies with lower credit ratings to increase liquidity. Conversion bonds rely on qualitative judgment in the past, although decision-making on whether and when to exercise the right to convert is the most important issue. Therefore, this paper proposes to apply artificial neural network techniques to scientifically determine the exercise of conversion rights. We distinguish between a total of 1,800 learning data published in the past and 200 predictive experimental data and build an artificial neural network learning model. As a result, the parity performance in most groups was excellent, achieving an average excess of about 10% or more. In particular, groups 3-6 recorded an average excess of about 20% and group 6 recorded an average excess of about 37%. This paper is meaningful in that it focused on solving decision problems by converging and applying machine learning techniques, a representative technology of the fourth industry, to the financial sector.

• Information and Communications Magazine
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• v.20 no.11
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• pp.1550-1559
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• 2003

The convergence of fixed and wireless networks in data communication is providing the necessary driver for M2M commerce to take-off. The opportunities provided by M2M Commerce areonly limited by imagination. Automotive Fleet and Freight, Tolling, Water and Power Metering, Supply Chain Management including Asset Management, Remote Monitoring and Diagnostics, Energy Management and Access Control and Security are among the many M2M applications that are currently getting rolled out. ARC Group expects the worldwide solutions market to be worth in excess of US$ 100 billion by 2007. In addition, operator revenues worldwide from the transport of Telematics data alone will rise from US$ 3.5 billion in 2002 to US$ 78 billion by 2007. This paper discusses some of the lifestyle and business opportunities provided by M2M Commerce in the new ear of network convergence. It also provides some case studies to demonstrate the benefits of M2M Commerce across the supply chain. The key focus of the paper is on achieving enhanced lifestyle, cost reduction, improved profitability and enhanced customer relationship management through M2M Commerce.