• 제목/요약/키워드: Dynamic regression model

검색결과 252건 처리시간 0.026초

DMS 모델과 이중 스펙트럼 특징을 이용한 HMM에 의한 음성 인식 (HMM-based Speech Recognition using DMS Model and Double Spectral Feature)

  • 안태옥
    • 한국산학기술학회논문지
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    • 제7권4호
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    • pp.649-655
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    • 2006
  • 본 논문은 화자 독립의 음성인식을 위한 연구로써, DMS 모델에 의한 DMSVQ(Dynamic Multi-Section Vector Quantization) 코드북과 이중 스펙트럼 특징을 이용한 HMM(Hidden Markov Model) 음성인식 방법을 제안한다. 정적 스펙트럼 특징으로서는 LPC ?S스트럼 계수를 이용하였고, 동적 스펙트럼 특징으로는 LPC ?S스트럼의 회귀계수를 사용하였다. 이들 두개의 스펙트럼 특징들을 각각 VQ 코드북으로 양자화되고, DMS 모델을 이용한 HMM은 입력으로써 정적 스펙트럼 특징과 동적 스펙트럼 특징을 받아드림으로써 모델링된다. 제안된 방법에 의한 인식 실험은 기존의 다양한 인식 방법에 의한 인식 실험들과 비교를 위해 동일한 데이터와 조건 하에서 수행하였다. 실험 결과, 본 연구에서 제안한 방법이 기존의 방법들보다 우수한 방법임을 입증하였다.

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소셜네트워크게임에서 광고비와 고객 유형 변수간 동적 상호관계 (Dynamic Interactive Relationships among Advertising Cost and Customer Types of Social Network Game)

  • 이희태
    • 유통과학연구
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    • 제14권4호
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    • pp.47-53
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    • 2016
  • Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

ARMA 모델을 이용한 적응 모델예측제어에 관한 연구 (Adaptive model predictive control using ARMA models)

  • 이종구;김석준;박선원
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.754-759
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    • 1993
  • An adaptive model predictive control (AMPC) strategy using auto-regression moving-average (ARMA) models is presented. The characteristic features of this methodology are the small computer memory requirement, high computational speed, robustness, and easy handling of nonlinear and time varying MIMO systems. Since the process dynamic behaviors are expressed by ARMA models, the model parameter adaptation is simple and fast to converge. The recursive least square (RLS) method with exponential forgetting is used to trace the process model parameters assuming the process is slowly time varying. The control performance of the AMPC is verified by both comparative simulation and experimental studies on distillation column control.

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A polynomial mathematical tool for foundation-soil-foundation interaction

  • Sbartai, Badreddine
    • Geomechanics and Engineering
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    • 제23권6호
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    • pp.547-560
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    • 2020
  • This paper studies the dynamic foundation-soil-foundation interaction for two square rigid foundations embedded in a viscoelastic soil layer. The vibrations come from only one rigid foundation placed in the soil layer and subjected to harmonic loads of translation, rocking, and torsion. The required dynamic response of rigid surface foundations constitutes the solution of the wave equations obtained by taking account of the conditions of interaction. The solution is formulated using the frequency domain Boundary Element Method (BEM) in conjunction with the Kausel-Peek Green's function for a layered stratum, with the aid of the Thin Layer Method (TLM), to study the dynamic interaction between adjacent foundations. This approach allows the establishment of a mathematical model that enables us to determine the dynamic displacements amplitude of adjacent foundations according to their different separations, the depth of the substratum, foundations masss, foundations embedded, and the frequencies of excitation. This paper attempts to introduce an approach based on a polynomial mathematical tool conducted from several results of numerical methods (BEM-TLM) so that practicing civil engineers can evaluation the dynamic foundations displacements more easy.

Animation of AVP and DAVP for Regression diagnostics

  • Park, Sung-H.;Kim, Jae-J.;Chung, Sung-H
    • Communications for Statistical Applications and Methods
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    • 제5권1호
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    • pp.1-18
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    • 1998
  • Since 1960s, in which the computer graphics system first appeared, various graphical techniques have been introduced for regression diagnostics and they have been remarkably developed. In particular, animation, one of the dynamic graphical methods which Cook and Weisberg (1989) proposed helps to show the effect of adding variables or observations to a model, or removing them from a model on the regression results. We present the added variable plots (AVP) with animation, which can be used as an optical tool of understanding the affect of some variables or observations on other variables, and the detrended added-variable plots (DAVP) with animation, through which it is possible to find out whether specific variables or observations have an effect on the nonlinearity of other variables or not.

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동적 그림을 이용한 이상치 검색 (Outlier Detection Using Dynamic Plots)

  • 안병진;서한손
    • 응용통계연구
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    • 제24권5호
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    • pp.979-986
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    • 2011
  • 선형회귀모형분석은 방법의 간편성과 높은 적용성에 의해 다양한 종류의 자료 분석에 활용되고 있다. 하지만 자료에 이상치가 포함되는 경우 이에 민감하게 영향을 받게 되므로 의심되는 관찰치를 찾아서 이상치 여부를 검토하는 것이 중요하다. 그러나 이상치를 탐지하는 방법의 대부분은 가면화 효과 등 이상치로부터 영향을 받아 정확하게 이상치를 발견하지 못하는 경우가 있다. 본 연구에서는 이를 개선하기 위하여 동적 잔차도를 활용한 방법을 제안한다. 제안된 방법은 종속적 이상치탐지방법을 사용할 때 다양한 기초군을 제공하는데 유용하며 결과적으로 정확한 이상치군을 탐지하게 되는 것을 예를 통해 검증한다.

Advanced Process Control of the Critical Dimension in Photolithography

  • Wu, Chien-Feng;Hung, Chih-Ming;Chen, Juhn-Horng;Lee, An-Chen
    • International Journal of Precision Engineering and Manufacturing
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    • 제9권1호
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    • pp.12-18
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    • 2008
  • This paper describes two run-to-run controllers, a nonlinear multiple exponential-weight moving-average (NMEWMA) controller and a dynamic model-tuning minimum-variance (DMTMV) controller, for photolithography processes. The relationships between the input recipes (exposure dose and focus) and output variables (critical dimensions) were formed using an experimental design method, and the photolithography process model was built using a multiple regression analysis. Both the NMEWMA and DMTMV controllers could update the process model and obtain the optimal recipes for the next run. Quantified improvements were obtained from simulations and real photolithography processes.

Multiprocess Dynamic Survival Models with Numbers of Deaths

  • Joo Yong Shim;Joong Kweon Sohn;Sang Gil Kang
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.567-576
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    • 1996
  • The multiprocess dynamic survival model is proposed for the application of the regression model on the analysis of survival data with time-varying effects of covariates : where the survival data consists of numbers of deaths at certain time-points. The algorithm for the recursive estimation of a time-varying parameter vector is suggested. Also the algorithm of forecasting of numbers of deaths of each group in the next time interval based on the information gathered until the end of current time interval is suggested.

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No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

  • Kim, Hyoung-Gook;Shin, Seung-Su;Kim, Sang-Wook;Lee, Gi Yong
    • ETRI Journal
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    • 제43권3호
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    • pp.538-548
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    • 2021
  • This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

이송물체의 질량 측정 속도 및 정밀도 향상 모사 연구

  • 이우갑;정진완;김광표
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1992년도 추계학술대회 논문집
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    • pp.161-165
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    • 1992
  • The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.