• 제목/요약/키워드: discrete data

검색결과 1,244건 처리시간 0.031초

Discrete bacterial foraging optimization for resource allocation in macrocell-femtocell networks

  • Lalin, Heng;Mustika, I Wayan;Setiawan, Noor Akhmad
    • ETRI Journal
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    • 제40권6호
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    • pp.726-735
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    • 2018
  • Femtocells are good examples of the ultimate networking technology, offering enhanced indoor coverage and higher data rate. However, the dense deployment of femto base stations (FBSs) and the exploitation of subcarrier reuse between macrocell base stations and FBSs result in significant co-tier and cross-tier interference, thus degrading system performance. Therefore, appropriate resource allocations are required to mitigate the interference. This paper proposes a discrete bacterial foraging optimization (DBFO) algorithm to find the optimal resource allocation in two-tier networks. The simulation results showed that DBFO outperforms the random-resource allocation and discrete particle swarm optimization (DPSO) considering the small number of steps taken by particles and bacteria.

예비 수학교사들이 이산수학 학습에서 겪는 어려움 분석 (A Study on the Difficulties of Pre-service Mathematics Teachers in the Discrete Mathematics Learning)

  • 임해미;전영주
    • 한국학교수학회논문집
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    • 제23권1호
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    • pp.89-109
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    • 2020
  • 본 연구는 예비 수학교사들이 이산수학 학습에서 겪는 어려움의 원인과 배경을 조사·분석하여 교사 교육 개선에 도움을 주고자 함이다. 이를 위해 예비교사를 대상으로 이산수학 교과목에 대한 설문과 지필평가를 실시하고 여기서 얻은 자료를 분석하였다. 그 결과 첫째, 이산수학 교육의 필요성에 대한 예비교사들의 가치 인식 공유가 요구된다. 둘째, 이산수학 내용요소의 적정성 및 이수 시수의 검토가 필요하다. 셋째, 예비 수학교사들이 갖는 학습 곤란의 발생 원인을 학습요인 이외의 측면에서 살펴볼 필요가 있다. 그리고 중등 학교수학과 대학의 이산수학 교육과정 연속성 측면에서 내용요소의 체계성, 계열성 연구가 필요하다는 것과 중등임용에서의 이산수학 출제 비율 조정에 대한 신중한 고려가 요구된다는 시사점을 도출하였다.

최소자승법에 의한 ABS(Antilock Braking System)의 모델링 및 파라미터 평가 (Modeling and Parameter estimation of Antilock Braking System)

  • 송창섭;노형우
    • 한국정밀공학회지
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    • 제19권4호
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    • pp.87-92
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    • 2002
  • By using the signal error test, model structure of total antilock braking system consisting of electromagnetic system and hydraulic system is determined as 9th order system. For determining parameters of the ABS, using time discrete model of parametric method, parameters in time discrete model are searched by least square method. By bilinear transform, we have found the model of ABS in s domain. Afterward, experimental output data is compared with simulated output data by MATLAB haying identified parameter. As the result, experimental data is agreed with simulated data very well.

Compressive sensing-based two-dimensional scattering-center extraction for incomplete RCS data

  • Bae, Ji-Hoon;Kim, Kyung-Tae
    • ETRI Journal
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    • 제42권6호
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    • pp.815-826
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    • 2020
  • We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

이동로봇의 시각센서를 위한 동영상 압축기 구현 (Implementation of Visual Data Compressor for Vision Sensor of Mobile Robot)

  • 김형오;조경수;백문열;기창두
    • 한국정밀공학회지
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    • 제22권9호
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    • pp.99-106
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    • 2005
  • In recent years, vision sensors are widely used to mobile robot for navigation or exploration. The analog signal transmission of visual data being used in this area, however, has some disadvantages including noise weakness in view of the data storage. A large amount of data also makes it difficult to use this method for a mobile robot. In this paper, a digital data compressing technology based on MPEG4 which substitutes for analog technology is proposed to overcome the disadvantages by using DWT(Discreate Wavelet Transform) instead of DCT(Discreate Cosine Transform). The TI Company's DSP chip, TMS320C6711, is used for the image encoder, and the performance of the proposed method is evaluated by PSNR(Peake Signal to Noise Rates), QP(Quantization Parameter) and bitrate.

퍼지 시스템을 위한 샘플치 데이터 상태 피드백 제어기 설계: 지능헝 디지털 재설계 접근 (Design of State Feedback Controller for Fuzzy Systems: Intelligent Digital Redesign)

  • 김도완;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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    • pp.2480-2482
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    • 2005
  • This paper presents a complete solution to intelligent digital redesign problem (IDR) for sampled-data fuzzy systems. The IDR problem is the problem of designing a sampled-data state feedback controller such that the sampled-data fuzzy system is equivalent to the continuous-time fuzzy system in the sense of the state matching. Its solution is simply obtained by linear transformation. Under the proposed sampled-data controller, the states of the discrete-time model of the sampled-data fuzzy system completely matches the state of the discrete-time model of the closed-loop continuous-time fuzzy systems are completely matched at every sampling points.

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Evaluation of Attribute Selection Methods and Prior Discretization in Supervised Learning

  • Cha, Woon Ock;Huh, Moon Yul
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.879-894
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    • 2003
  • We evaluated the efficiencies of applying attribute selection methods and prior discretization to supervised learning, modelled by C4.5 and Naive Bayes. Three databases were obtained from UCI data archive, which consisted of continuous attributes except for one decision attribute. Four methods were used for attribute selection : MDI, ReliefF, Gain Ratio and Consistency-based method. MDI and ReliefF can be used for both continuous and discrete attributes, but the other two methods can be used only for discrete attributes. Discretization was performed using the Fayyad and Irani method. To investigate the effect of noise included in the database, noises were introduced into the data sets up to the extents of 10 or 20%, and then the data, including those either containing the noises or not, were processed through the steps of attribute selection, discretization and classification. The results of this study indicate that classification of the data based on selected attributes yields higher accuracy than in the case of classifying the full data set, and prior discretization does not lower the accuracy.

Experimental evaluation of discrete sliding mode controller for piezo actuated structure with multisensor data fusion

  • Arunshankar, J.;Umapathy, M.;Bandhopadhyay, B.
    • Smart Structures and Systems
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    • 제11권6호
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    • pp.569-587
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    • 2013
  • This paper evaluates the closed loop performance of the reaching law based discrete sliding mode controller with multisensor data fusion (MSDF) in real time, by controlling the first two vibrating modes of a piezo actuated structure. The vibration is measured using two homogeneous piezo sensors. The states estimated from sensors output are fused. Four fusion algorithms are considered, whose output is used to control the structural vibration. The controller is designed using a model identified through linear Recursive Least Square (RLS) method, based on ARX model. Improved vibration suppression is achieved with fused data as compared to single sensor. The experimental evaluation of the closed loop performance of sliding mode controller with data fusion applied to piezo actuated structure is the contribution in this work.

Outlier Detection Based on Discrete Wavelet Transform with Application to Saudi Stock Market Closed Price Series

  • RASHEDI, Khudhayr A.;ISMAIL, Mohd T.;WADI, S. Al;SERROUKH, Abdeslam
    • The Journal of Asian Finance, Economics and Business
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    • 제7권12호
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    • pp.1-10
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    • 2020
  • This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

A Modified Method Based on the Discrete Sliding Norm Transform to Reduce the PAPR in OFDM Systems

  • Salmanzadeh, R.;Mozaffari Tazehkand, B.
    • ETRI Journal
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    • 제36권1호
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    • pp.42-50
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    • 2014
  • Orthogonal frequency division multiplexing (OFDM) is a modulation technique that allows the transmission of high data rates over wideband radio channels subject to frequency selective fading by dividing the data into several narrowband and flat fading channels. OFDM has high spectral efficiency and channel robustness. However, a major drawback of OFDM is that the peak-to-average power ratio (PAPR) of the transmitted signals is high, which causes nonlinear distortion in the received data and reduces the efficiency of the high power amplifier in the transmitter. The most straightforward method to solve this problem is to use a nonlinear mapping algorithm to transform the signal into a new signal that has a smaller PAPR. One of the latest nonlinear methods proposed to reduce the PAPR is the $L_2$-by-3 algorithm, which is based on the discrete sliding norm transform. In this paper, a new algorithm based on the $L_2$-by-3 method is proposed. The proposed method is very simple and has a low complexity analysis. Simulation results show that the proposed method performs better, has better power spectral density, and is less sensitive to the modulation type and number of subcarriers than $L_2$-by-3.