• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.343-344
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• 2007

In this paper, we study the signed-DLMS adaptive algorithm of wireless repeater for solving shadow region due to propagation between base station and mobile station. The the signed-DLMS algorithm reduces interference signals from multipath and solves the oscillation problem of repeater by estimation and cancellation. To efficiently reject interference signal, the signed-DLMS adaptive algorithm is applied. The computational complexities of the signed-DLMS are reduced verse standard LMS algorithm. Wireless ICS repeater based on signed-DLMS reduces the cost and is able to increase channel capacities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.193-197
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• 2015

Recently, the new issues for the safety and the information delivery system in the ship are raised. The deployment and the efficient algorithms of deploying the wireless sensor networks instead of using the built-in wired networks or the setup of the new wired networks is more desirable than the deployment of the wired networks in a ship after its final production since it can reduce the cost and the time of the brand new wired networks by reshaping some of the internal structure of the ship. In this paper, the shipboard signal propagation measurement system based on the signature sequence-three way slave mode are designed and its measureed data are analysed after measuring the signal propagation characteristics. Consequently, it is expected that the reliable and cost-effective signal measurement system with the three way algorithm for the deployment of the shipboard wireless networks can be achieved.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.445-458
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• 2001

The shape and the distribution of material construction of the scatterer may be obtained from its scattered fields by the iterative inversion in the spectral domain. The illposedness, the resolution, and the uniqueness of the inversion are the key problems in the inversion and inter-related. The illposedness is shown to be caused by the evanescent modes which carries and amplifies exponentially the measurement errors in the back-propagation of the measured scattered fields. By filtering out all the evanescent modes in the cost functional defined as the squared difference between the measured and the calculated spatial spectrum of the scattered fields from the iteratively chosen medium parameters of the scatterer, one may regularize the illposedness of the inversion in the expense of the resolution. There exist many local minima of the cost functional for the inversion of the large and the high-contrast scatterer and the hybrid algorithm combining the genetic algorithm and the Levenberg-Marquardt algorithm is shown to find efficiently its global minimum. The resolution of reconstruction obtained by keeping all the propating modes and filtering out the evanescent modes for the regularization becomes 0.5 wavelength. The super resolution may be obtained by keeping the evanescent modes when the measurement error and instance, respectively, are small and near.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.184-190
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• 2006

Recently, Lee et al. have proposed an algorithm utilizing the signals from different paths by using bottom mounted simple linear array to estimate 3-D location of oceanic target. But this algorithm assumes that sound velocity is constant along depth of sea. Consequently, serious performance loss is appeared in real oceanic environment that sound speed is changed variously. In this paper, we present a 3-D near field localization algorithm for inhomogeneous sound speed. The proposed algorithm adopt localization function that utilize ray propagation model for multipath environment with linear sound speed profile(SSP), after that, the proposed algorithm searches for the instantaneous azimuth angle, range and depth from the localization cost function. Several simulations using linear SSP and non linear SSP similar to that of real oceans are used to demonstrate the performance of the proposed algorithm. The estimation error in range and depth is decreased by 100m and 50m respectively.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.64-70
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• 2003

This paper suggests a systematic methodology to predict chip forms using the experimental design technique and the neural network. Significant factors determined with ANOVA analysis are used as input variables of the neural network back-propagation algorithm. It has been shown that cutting conditions and cutting tool shapes have distinct effects on the chip forms, so chip breaking. Cutting tools are represented using the Z-map method, which differs from existing methods using some chip breaker parameters. After training the neural network with selected input variables, chip forms are predicted and compared with original chip forms obtained from experiments under same input conditions, showing that chip forms are same at all conditions. To verify the suggested model, one tool not used in training the model is chosen and input to the model. Under various cutting conditions, predicted chip forms agree well with those obtained from cutting experiments. The suggested method could reduce the cost and time significantly in designing cutting tools as well as replacing the“trial-and-error”design method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.147-152
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• 2012

This paper estimates the direction of arrival of desired a target using propagation wave in spatial. Direction of arrival estimation is to find desired target position among received signal to receiver array antennas. In this paper, we estimated direction of arrival for target, by using cost function and high resolution MUSIC algorithm, in order to direction of arrival estimation, and calculated optimum weight vector. Through simulation, in regard to the estimation of the arrival direction of a target, the performances of the existing ESPRIT algorithm and the proposed algorithm were comparatively analyzed. In the estimation time of the arrival direction of a target object, the proposed algorithm showed an improvement of approximately as compared to the existing ESPRIT algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.1-6
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• 2001

This paper proposes a pattern classification method of interval vectors by interval neural networks. The proposed method can be applied to pattern classification where attribute values of each sample are given as interval numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Next, a learning algorithm is derived from the cost function. a cost function is defined using the interval output from the interval neural network and the corresponding target output. Last, using numerical examples, the proposed approach is illustrated and compared with other approach based on the standard back-propagation neural networks.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.150-160
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• 2011

IT convergence and integration technology aims to create new synergies by combining IT related technology and performance. This study conducted a basic research for combining construction and IT technology to create new synergies. Specifically, the purpose of this study is to combine USN and GIS technology and then apply it to urban facilities management. For this, we have developed the USN hardware, tested propagation communications, and made the GIS Algorithm and a system. Existing sensor node allocation method is mostly to install in a random way or with in-situ survey, but the problem with this method is contradictory to cost effectiveness and efficiency. To solve this problem, we developed a new method for sensor allocation. Using this method, the USN technology could be applied in the range of city unit. This technology can be applied to the ubiquitous urban development such as U-City and Smart City.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.168-171
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• 2016

In recent years, indoor localization in Wi-Fi environment has been researched for its location determining capability. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs had the lowest average error in all 4 scenarios with 3.99 meters.