• Title/Summary/Keyword: 근사화 기법

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Reliability Analysis of Slopes Using ANN-based Limit-state Function (인공신경망 기반의 한계상태함수를 이용한 사면의 신뢰성해석)

  • Cho, Sung-Eun;Byeon, Wi-Yong
    • Journal of the Korean Geotechnical Society
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    • v.23 no.8
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    • pp.117-127
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    • 2007
  • Slope stability analysis is a geotechnical engineering problem characterized by many sources of uncertainty. Some of them are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for integrating commercial finite difference method into probabilistic analysis of slope stability is presented. Since the limit-state function cannot be expressed in an explicit form, the ANN-based response surface method is adopted to approximate the limit-state function and the first-, second-order reliability method and the Monte Carlo simulation technique are used to calculate the probability of failure. Probabilistic stability assessments for a hypothetical two-layer slope and the Sugar Creek embankment were performed to verify the application potential to the slope stability problems. The examples show the successful implementation and the possibility of the extension of the proposed procedure to the variety of geotechnical engineering problems.

IMBE Model Based SNR Estimation of Continuous Speech Signals (연속음성신호에서 IMBE 모델을 이용한 SNR 추정 연구)

  • Park, Hyung-Woo;Bae, Myung-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.2
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    • pp.148-153
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    • 2010
  • In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.

Energy-Dependent Preemphasis for Speech Signal Preprocessing (음성신호 전처리를 위한 에너지 의존 프리엠퍼시스)

  • Kim, Dong-Jun;Park, Sang-Hui
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.3
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    • pp.18-25
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    • 1997
  • This study describes a modified preemphasis formula, what we call energy-dependent preemphasis(EDP). This uses the normalized short-term energy of speech signal, with the assumption that the source characteristics of the glottal pulses and the radiation characteristics of the lips are approximately proportional to the energy of speech signal. Using this method, speech analyses, such as AR spectrum estimation, formant detection, are performed for nonstationary starting parts of 5 Korean single vowels. The results are compared with the conventional two preemphasis methods. We found that the proposed preemphasis gave enhanced spectral shapes and more accurate formant frequencies and avoided overlapping phenomenon of adjacent two formants.

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Qualitative Evaluation by using Intelligent Fuzzy Logical Inference for the Public Education (지능형 퍼지 추론 기법을 적용한 공교육의 정성 평가방법)

  • Kim, Youngtaek
    • The Journal of Korean Association of Computer Education
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    • v.17 no.1
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    • pp.97-105
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    • 2014
  • To enhance the practical usage of solely quantitative evaluation method for each students on the current public education fields which might cause some social problems, an intelligent and adaptive fuzzy logical inference methodology for the additional qualitative evaluation technique is proposed to utilize each students personal characteristic properties to be evaluated. Proposed method uses some verbal descriptions for the linguistic qualifier in addition to the grade points. An imaginary virtual experimentation only has been implemented due to some difficulties with the critical national educational policy problems in the case of some possibly real and practical experimental environments to be utilized for the simulation.

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Waveform inversion of shallow seismic refraction data using hybrid heuristic search method (하이브리드 발견적 탐색기법을 이용한 천부 굴절법 자료의 파형역산)

  • Takekoshi, Mika;Yamanaka, Hiroaki
    • Geophysics and Geophysical Exploration
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    • v.12 no.1
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    • pp.99-104
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    • 2009
  • We propose a waveform inversion method for SH-wave data obtained in a shallow seismic refraction survey, to determine a 2D inhomogeneous S-wave profile of shallow soils. In this method, a 2.5D equation is used to simulate SH-wave propagation in 2D media. The equation is solved with the staggered grid finite-difference approximation to the 4th-order in space and 2nd-order in time, to compute a synthetic wave. The misfit, defined using differences between calculated and observed waveforms, is minimised with a hybrid heuristic search method. We parameterise a 2D subsurface structural model with blocks with different depth boundaries, and S-wave velocities in each block. Numerical experiments were conducted using synthetic SH-wave data with white noise for a model having a blind layer and irregular interfaces. We could reconstruct a structure including a blind layer with reasonable computation time from surface seismic refraction data.

Effect Analysis of Residual Frequency Offsets for Asynchronous MC-CDMA Uplink Systems (비동기 MC-CDMA 상향 링크 시스템에서의 잔류 주파수 옵셋 영향 분석)

  • Ko, Kyun-Byoung;Woo, Choong-Chae
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.8
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    • pp.9-15
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    • 2010
  • This paper presents an analysis of asynchronous multicarrier-code division multiple access (MC-CDMA) uplink systems over frequency-selective multipath fading channels when the frequency offsets (FOs) of all users are random variables and the frequency offset for the desired user is compensated. The effect of a residual frequency offset(RFO) on the average bit error rate (BER) is evaluated by the semi-analytical method, then the approximated BER performance is obtained as a closed-form expression. Moreover, the signal to noise ratio (SNR) loss caused by RFO is evaluated. Derived results show that the performance degradation due to RFO is negligible if the estimation error of RFO for the desired user is less than the normalized value of 0.1.

The Effects of Time Domain Windowing and Detection Ordering on Successive Interference Cancellation in OFDM Systems over Doubly Selective Channels (이중 선택적 채널 OFDM 시스템에서 시간 영역 윈도우와 검출 순서가 순차적 간섭 제거에 미치는 영향)

  • Lim, Dong-Min
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.21 no.6
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    • pp.635-641
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    • 2010
  • Time-varying channel characteristics in OFDM systems over doubly selective channels cause inter-carrier interferences(ICI) in the frequency domain. Time domain windowing gives rise to restriction on the bandwidth of the frequency domain channel matrix and makes it possible to approximate the OFDM system as a simplified linear input-output model. When successive interference cancellation based on linear MMSE estimation is employed for channel equalization in OFDM systems, symbol detection ordering produces considerable effects on overall system performances. In this paper, we show the reduction of the residual ICI by time domain windowing and the resultant performance improvements, and investigate the effects of SINR- and CSEP-based symbol detection ordering on the performance of successive interference cancellation.

A study on Modified Method of Orthogonal Neural Network for Nonlinear system approximation (비선형 시스템의 근사화를 위한 직교 신경망의 수정 기법에 관한 연구)

  • 김성식;이영석
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.33-40
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    • 1998
  • This paper presents an Modified Orthogonal Neural Network(MONN), new modified model of Orthogonal Neural Network(0NN) based on orthogonal functions, and applies it to nonlinear system approximator. ONN proposed by Yang and Tseng, doesn't have the problems of traditional multilayer feedforward neural networks such as the determination of initial weights and the numbers of layers and processing elements. And tranining of ONN converges rapidly. But ONN cannot adapt its orthogonal functions to a given system. The accuracy of ONN, in terms of the minimal possible deviation between system and approximator, is essentially dependent on the choice of basic orthogonal functions. In order to improve ability and effectiveness of approximate nonlinear systems, MONN has an input transformation layer to adapt its basic orthogonal functions to a given nonlinear system. The results show that MONN has the excellent performance of approximate nonlinear systems and the input transfnrmation makes the ability of MONN better than one of ONN.

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An Approximate Reconstruction of NPT for Synchronized Data Broadcasting (동기화된 데이터방송을 위한 근사적인 NPT 재구성 기법)

  • 정문열;김용한;백두원
    • Journal of Broadcast Engineering
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    • v.9 no.1
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    • pp.83-90
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    • 2004
  • DVB-MHP recommends that NPT(normal play time) be used as the times of stream events. NPT is the local time within an event(TV program). But we found that commercial transport stream (TS) generators and middlewares for DVB-MHP settop boxes are not ready to support the use of NPT by applications. In particular, TS generators do not create NPT reference descriptors needed to reconstruct NPT at the TV receiver. This situation is undesirable because program providers cannot experiment with the idea of synchronized applications. So we have implemented a TS generator that inserts NPT reference descriptors to TS and MyGetNPT API to approximately reconstruct NPT. STC (system time clock) is needed to reconstruct NPT, but Xlets are not allowed to read it. So, we approximate STC by using PCR (program clock reference) and the Java system tune. In this method, the stream generator extrats PCRs from an existing TS and inserts them into null TS packets in the form of MPEG sections, which can be read by Xlets. Because PCRs are displaced into new positions in TS, their values should be adjusted based on the time intervals between the original positions and the new positions. We implemented a synchronized application by using our TS generator and MyGetNPT API, where the task of stream events are to display graphic images. We found that graphic images are displayed where 240 ㎳ from their intended time, where 240ms is a human tolerance for the synchronization skew between graphic image and video.

A Study on Condition Analysis of Revised Project Level of Gravity Port facility using Big Data (빅데이터 분석을 통한 중력식 항만시설 수정프로젝트 레벨의 상태변화 특성 분석)

  • Na, Yong Hyoun;Park, Mi Yeon;Jang, Shinwoo
    • Journal of the Society of Disaster Information
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    • v.17 no.2
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    • pp.254-265
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    • 2021
  • Purpose: Inspection and diagnosis on the performance and safety through domestic port facilities have been conducted for over 20 years. However, the long-term development strategies and directions for facility renewal and performance improvement using the diagnosis history and results are not working in realistically. In particular, in the case of port structures with a long service life, there are many problems in terms of safety and functionality due to increasing of the large-sized ships, of port use frequency, and the effects of natural disasters due to climate change. Method: In this study, the maintenance history data of the gravity type quay in element level were collected, defined as big data, and a predictive approximation model was derived to estimate the pattern of deterioration and aging of the facility of project level based on the data. In particular, we compared and proposed models suitable for the use of big data by examining the validity of the state-based deterioration pattern and deterioration approximation model generated through machine learning algorithms of GP and SGP techniques. Result: As a result of reviewing the suitability of the proposed technique, it was considered that the RMSE and R2 in GP technique were 0.9854 and 0.0721, and the SGP technique was 0.7246 and 0.2518. Conclusion: This research through machine learning techniques is expected to play an important role in decision-making on investment in port facilities in the future if port facility data collection is continuously performed in the future.