• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.305-309
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• 2011

A sparse reconfigurable adaptive filter (SRAF) based on a photonic switch determines the appropriate time delays and weight values for an optical switch implementation of tapped-delay-line (TDL) systems. It is well known that the choice of switch delays is significantly important for efficiently implementing the SRAF. If the same values exist as calculating the sum of weight magnitudes for implementing the connection constraint required by the SRAF, conventional connection algorithm based on sequentially selection the maximum elements might not work perfectly. In an effort to increase the effectiveness of system identification, an upgraded connection algorithm used progressive calculation to obtain the better solution is considered in this paper. The performance of the proposed connection constraint algorithm is illustrated by computer simulation for a system identification application.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.368-376
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• 2007

The large potential bandwidth available in wavelength-division multiplexed optical networks makes this technology of crucial importance for satisfying the ever increasing capacity requirements of the next-generation Internet. In this scenario, the routing and wavelength assignment(RWA) problem that concerns determining the optical paths and wavelengths to be used for connection establishment in a wavelength-routed network, is still one of the most important open issues. In this paper we propose a new online dynamic grooming-capable RWA heuristic scheme working on wavelength division multiplexing(WDM) networks as a multistage selection process. The proposed algorithm is transparent with respect to the presence of wavelength converters, achieves very low connection rejection ratios with minimal computational complexity and is appropriate for the modern multilayer optical circuit and wavelength switched networks with sparse wavelength conversion capability.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.13-20
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• 2001

Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.259-261
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• 2008

GIS-based spatial data integration tasks have used exhaustive thematic maps generated from sparsely sampled data or satellite-based exhaustive data. Due to a simplification of reality and error in mapping procedures, such spatial data are usually imperfect and of different accuracy. The objective of this study is to carry out a sensitivity analysis in connection with input topographic data for landslide hazard mapping. Two different types of elevation estimates, elevation spot heights and a DEM from ASTER stereo images are considered. The geostatistical framework of kriging is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. The effects of different accuracy arising from different terrain-related maps on the prediction performance of landslide hazard are illustrated from a case study of Boeun, Korea.

• Smart Structures and Systems
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• v.15 no.1
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• pp.81-97
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• 2015

Recently, a new output-only modal identification method based on time-frequency independent component analysis (ICA) has been developed by the authors and shown to be useful for even highly-damped structures. In many cases, it is of interest to identify the complex modes of structures with non-proportional damping. This study extends the time-frequency ICA based method to a complex ICA formulation for output-only modal identification of non-proportionally-damped structures. The connection is established between complex ICA model and the complex-valued modal expansion with sparse time-frequency representation, thereby blindly separating the measured structural responses into the complex mode matrix and complex-valued modal responses. Numerical simulation on a non-proportionally-damped system, laboratory experiment on a highly-damped three-story frame, and a real-world highly-damped base-isolated structure identification example demonstrate the capability of the time-frequency complex ICA method for identification of structures with complex modes in a straightforward and efficient manner.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.1-7
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• 2021

In this paper, we presented the experimental basis for the theoretical background and robustness of the Convolutional Neural Network for object recognition based on artificial intelligence. An experimental result was performed to visualize the weighting filters and feature maps for each layer to determine what characteristics CNN is automatically generating. experimental results were presented on the trend of learning error and identification error rate by checking the relevance of the weight filter and feature map for learning error and identification error. The weighting filter and characteristic map are presented as experimental results. The automatically generated characteristic quantities presented the results of error rates for moving and rotating robustness to geometric changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2711-2733
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• 2018

Minimizing power consumption in bandwidth limited optical traffic grooming networks is presented as a two-objective optimization problem. Since the main objective is to route a connection, the network throughput is maximized first, and then the minimum power consumption solution is found for this maximized throughput. Both transparent IP over WDM (Tp-IPoWDM) and translucent IP over WDM (Tl-IPoWDM) network may be applied to examine such bi-objective algorithms. Simulations show that the bi-objective algorithms are more energy-efficient than the single objective algorithms where only the throughput is optimized. For a Tp-IPoWDM network, both link based ILP (LB-ILP) and path based ILP (PB-ILP) methods are formulated and solved. Simulation results show that PB-ILP can save more power than LB-ILP because PB-ILP has more path selections when lightpath lengths are limited. For a Tl-IPoWDM network, only PB-ILP is formulated and we show that the Tl-IPoWDM network consumes less energy than the Tp-IPoWDM network, especially under a sparse network topology. For both kinds of networks, it is shown that network energy efficiency can be improved by over-provisioning wavelengths, which gives the network more path choices.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.383-396
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• 2004

The application of spatial statistics to obtain the spatial uncertainty distributions in classification of remote sensing images is investigated in this paper. Two quantitative methods are presented for describing two kinds of uncertainty; one related to class assignment and the other related to the connection of reference samples. Three quantitative indices are addressed for the first category of uncertainty. Geostatistical simulation is applied both to integrate the exhaustive classification results with the sparse reference samples and to obtain the spatial uncertainty or accuracy distributions connected to those reference samples. To illustrate the proposed methods and to discuss the operational issues, the experiment was done on a multi-sensor remote sensing data set for supervised land-cover classification. As an experimental result, the two quantitative methods presented in this paper could provide additional information for interpreting and evaluating the classification results and more experiments should be carried out for verifying the presented methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.29-39
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• 2008

Greedy routing which is easy to apply to geographic wireless sensor networks is frequently used. Greedy routing works well in dense networks whereas in sparse networks it may fail. When greedy routing fails, it needs a recovery algorithm to get out of the communication void. However, additional recovery algorithm causes problems that increase both the amount of packet transmission and energy consumption. Communication void is a condition where all neighbor nodes are further away from the destination than the node currently holding a packet and it therefore cannot forward a packet using greedy forwarding. Therefore we propose a VODUA(Virtually Ordered Distance Upgrade Algorithm) as a novel idea to improve and solve the problem of void. In VODUA, nodes exchange routing graphs that indicate information of connection among the nodes and if there exist a stuck node that cannot forward packets, it is terminated using Distance Cost(DC). In this study, we indicate that packets reach successfully their destination while avoiding void through upgrading of DC. We designed the VODUA algorithm to find valid routes through faster delivery and less energy consumption without requirement for an additional recovery algorithm. Moreover, by using VODUA, a network can be adapted rapidly to node's failure or topological change. This is because the algorithm utilizes information of single hop instead of topological information of entire network. Simulation results show that VODUA can deliver packets from source node to destination with shorter time and less hops than other pre-existing algorithms like GPSR and DUA.