• The Journal of Information Technology
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• v.8 no.1
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• pp.51-56
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• 2005

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.672-676
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• 2010

This paper presents a learning rule that weights more on data near decision boundary. This learning rule generates better decision boundary by reducing the effect of outliers on the decision boundary. The proposed learning rule is integrated into IAFC neural network. IAFC neural network is stable to maintain previous learning results and is plastic to learn new data. The performance of the proposed fuzzy neural network is compared with performances of LVQ neural network and backpropagation neural network. The results show that the performance of the proposed fuzzy neural network is better than those of LVQ neural network and backpropagation neural network.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1333-1339
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• 2009

A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.591-593
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• 1995

Artificial neural network based pattern recognition method is one of the most probable candidate for on-line power system transient stability analysis. Especially, Kohonen layer is an adequate neural network for the purpose. Each node of Kehonen layer competes on the basis of which of them has its clustering center closest to an input vector. This paper discusses Kohonen's LVQ(Learning Victor Quantization) and points out a defection of the algorithm when applied to the transient stability analysis. Only the clustering centers located near the decision boundary of the stability region is needed for the stability criterion and the centers far from the decision boundary are redundant. This paper presents a new algorithm ratted boundary searching algorithm II which assigns only the points that are near the boundary in an input space to nodes or Kohonen layer as their clustering centers. This algorithm is demonstrated with satisfaction using 4-generator 6-bus sample power system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.88-96
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• 2007

H.264 is a new international video coding standard that can achieve considerably higher coding efficiency than conventional standards. Its coding gain has been achieved by employing advanced video coding methods. Specially, the increased number of macroblock modes and the complex mode decision procedure using the Lagrangian optimization are the main factors for increasing coding efficiency. Although H.264 obtains improved coding efficiency, it is difficult to do an real-time encoding because it considers all coding parameters in the mode decision procedure. In this paper, we propose a fast mode decision algorithm which classifies the macroblock modes in order to determine the optimal mode having low complexity quickly. Simulation results show that the proposed algorithm can reduce the encoding time by 34.95% on average without significant PSNR degradation or bit-rate increment. In addition, in order to show the validity of simulation results, we set up a low boundary condition for coding efficiency and complexity and show that the proposed algorithm satisfies the low boundary condition.

• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.17-35
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• 2014

There is no provision regarding the 'litigation on land boundary' under the Korean laws. Therefore, there are disputes in theory with respect to its nature, requirements for litigation, criteria for determination, etc., and it is necessary to establish the provisions of the law on this issue in the future. For this legislation, it is necessary to conduct a comparative consideration on laws of other countries which have completed the relevant provisions. This study, as a first step, researches a history of litigation for determination of boundary under the Roman law and medieval law, and furthermore introduces the German law which has relatively completed legal provisions on litigation for determination of boundary. In addition to common ownership litigation, the German law has established a provision on litigation for boundary as a judicial procedure considering a special place, called as a dispute on ownership of adjacent land, on the assumption that it is difficult or impossible to prove the boundary. The primary purpose of this litigation is to clarify a true boundary, and if such clarification is impossible, a boundary is discretionally created in accordance with the statutory standards under Article 920 of the German Civil Act (BGB). It means creation of the scope of land ownership by operation of decision, not only by the 'discovery of original boundary'. Both cases are different from each other in the aspect of judicial decision, but embracing them into one is a lawsuit for determination of boundary under the German law. Under the Korean legislation, it is necessary to make a theory containing two different criteria for determination into a single type of litigation, considering such aspects.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.35-44
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• 1997

In this paper, a an algorithm that detects the endocardial boundary, expanding the region from endocardial cavity using fuzzy inference, is proposed. This algorithm decides the ventricular cavity by fuzzy inference in process of searching each pixel from the inside of left ventricle in echocardial image and expands it. Uncertainty and fuzziness exists in decision of endocardial boundary. Therefore, we convert the lingustic representation of mean, standard deviation, and threshold value that are characteristic variables of endocardial boundary to fuzzy input and output variables. And, we extract proposed method is robuster to noise than radial searching method that is highly dependent on center position. To prove the similarity of detected boundary by fuzzy nference, we used the measures of SIZE, correlation coefficient, MSD, and RMSE and had acquired reasonable results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.149-150
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• 2012

This paper presents a shot boundary detection method based on the global decision tree that allows for extraction of boundaries of high variations occurring due to camera breaks from frame difference values. For a start, difference values between frames are calculated through local X2-histogram and normalization. Next, the distances between difference values are calculated through normalization.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.89-102
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• 2013

The paper presents a fuzzy based impulse noise filter for both gray scale and color images. The proposed approach is based on the technique of boundary discriminative noise detection. The algorithm is a multi-step process comprising detection, filtering and color correction stages. The detection procedure classifies the pixels as corrupted and uncorrupted by computing decision boundaries, which are fuzzified to improve the outputs obtained. In the case of color images, a correction term is added by examining the interactions between the color components for further improvement. Quantitative and qualitative analysis, performed on standard gray scale and color image, shows improved performance of the proposed technique over existing state-of-the-art algorithms in terms of Peak Signal to Noise Ratio (PSNR) and color difference metrics. The analysis proves the applicability of the proposed algorithm to random valued impulse noise.