• Title/Summary/Keyword: statistical representation

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A Low-Cost Lidar Sensor based Glass Feature Extraction Method for an Accurate Map Representation using Statistical Moments (통계적 모멘트를 이용한 정확한 환경 지도 표현을 위한 저가 라이다 센서 기반 유리 특징점 추출 기법)

  • An, Ye Chan;Lee, Seung Hwan
    • The Journal of Korea Robotics Society
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    • v.16 no.2
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    • pp.103-111
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    • 2021
  • This study addresses a low-cost lidar sensor-based glass feature extraction method for an accurate map representation using statistical moments, i.e. the mean and variance. Since the low-cost lidar sensor produces range-only data without intensity and multi-echo data, there are some difficulties in detecting glass-like objects. In this study, a principle that an incidence angle of a ray emitted from the lidar with respect to a glass surface is close to zero degrees is concerned for glass detection. Besides, all sensor data are preprocessed and clustered, which is represented using statistical moments as glass feature candidates. Glass features are selected among the candidates according to several conditions based on the principle and geometric relation in the global coordinate system. The accumulated glass features are classified according to the distance, which is lastly represented on the map. Several experiments were conducted in glass environments. The results showed that the proposed method accurately extracted and represented glass windows using proper parameters. The parameters were empirically designed and carefully analyzed. In future work, we will implement and perform the conventional SLAM algorithms combined with our glass feature extraction method in glass environments.

A Markov Chain Representation of Statistical Process Monitoring Procedure under an ARIMA(0,1,1) Model (ARIMA(0,1,1)모형에서 통계적 공정탐색절차의 MARKOV연쇄 표현)

  • 박창순
    • The Korean Journal of Applied Statistics
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    • v.16 no.1
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    • pp.71-85
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    • 2003
  • In the economic design of the process control procedure, where quality is measured at certain time intervals, its properties are difficult to derive due to the discreteness of the measurement intervals. In this paper a Markov chain representation of the process monitoring procedure is developed and used to derive its properties when the process follows an ARIMA(0,1,1) model, which is designed to describe the effect of the noise and the special cause in the process cycle. The properties of the Markov chain depend on the transition matrix, which is determined by the control procedure and the process distribution. The derived representation of the Markov chain can be adapted to most different types of control procedures and different kinds of process distributions by obtaining the corresponding transition matrix.

Feature Extraction for Iris Recognition by Using Statistical Methods (통계적 홍채 특징 추출 방법)

  • 배광혁;이철한;노승인;김재희
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.61-64
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    • 2002
  • In this paper, we propose the iris feature extraction by using statistical methods. There are many approaches for iris feature extraction, but most of them require a set of parameters that one should choose for the transformation to obtain a useful representation of the iris. It would be most useful to estimate the method of the iris feature extraction from iris itself. Therefore, we apply the unsupervised statistical methods for the iris feature extraction.

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NETWORK DESIGN AND PREPROCESSING FOR MULTI-SCALE SPHERICAL BASIS FUNCTION REPRESENTATION

  • Oh, Hee-Seok;Kim, Dong-Hoh
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.209-228
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    • 2007
  • Given scattered surface air temperatures observed by a network of weather stations, it is an important problem to estimate the entire temperature field for every location on the globe. Recently, a multi-scale spherical basis function (SBF) representation was proposed by Li (1999) for representing scattered data on the sphere. However, for a successful application of Li (1999)'s method, some practical issues such as network design, bandwidth selection of SBFs and initial coefficients are to be resolved. This paper proposes automatic procedures to design network and to select bandwidths. This paper also considers a preprocessing problem to obtain a stable initial coefficients from scattered data. Experiments with real temperature data demonstrate the promising empirical properties of the proposed approaches.

A Hybrid Approach Using Case-based Reasoning and Fuzzy Logic for Corporate Bond Rating

  • Kim, Hyun-jung;Shin, Kyung-shik
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2003.05a
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    • pp.474-483
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    • 2003
  • A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

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Chinese Prosody Generation Based on C-ToBI Representation for Text-to-Speech (음성합성을 위한 C-ToBI기반의 중국어 운율 경계와 F0 contour 생성)

  • Kim, Seung-Won;Zheng, Yu;Lee, Gary-Geunbae;Kim, Byeong-Chang
    • MALSORI
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    • no.53
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    • pp.75-92
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    • 2005
  • Prosody Generation Based on C-ToBI Representation for Text-to-SpeechSeungwon Kim, Yu Zheng, Gary Geunbae Lee, Byeongchang KimProsody modeling is critical in developing text-to-speech (TTS) systems where speech synthesis is used to automatically generate natural speech. In this paper, we present a prosody generation architecture based on Chinese Tone and Break Index (C-ToBI) representation. ToBI is a multi-tier representation system based on linguistic knowledge to transcribe events in an utterance. The TTS system which adopts ToBI as an intermediate representation is known to exhibit higher flexibility, modularity and domain/task portability compared with the direct prosody generation TTS systems. However, the cost of corpus preparation is very expensive for practical-level performance because the ToBI labeled corpus has been manually constructed by many prosody experts and normally requires a large amount of data for accurate statistical prosody modeling. This paper proposes a new method which transcribes the C-ToBI labels automatically in Chinese speech. We model Chinese prosody generation as a classification problem and apply conditional Maximum Entropy (ME) classification to this problem. We empirically verify the usefulness of various natural language and phonology features to make well-integrated features for ME framework.

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An Orthogonal Representation of Estimable Functions

  • Yi, Seong-Baek
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.837-842
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    • 2008
  • Students taking linear model courses have difficulty in determining which parametric functions are estimable when the design matrix of a linear model is rank deficient. In this note a special form of estimable functions is presented with a linear combination of some orthogonal estimable functions. Here, the orthogonality means the least squares estimators of the estimable functions are uncorrelated and have the same variance. The number of the orthogonal estimable functions composing the special form is equal to the rank of the design matrix. The orthogonal estimable functions can be easily obtained through the singular value decomposition of the design matrix.

A Test Procedure for Change in Level Occurring at Unknown Points

  • Lee, Jae-Chang;Song, Il-Seong
    • Journal of the Korean Statistical Society
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    • v.18 no.1
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    • pp.38-45
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    • 1989
  • A procedure is considered to the problem of testing whether there exist changes in location at possibly two points in a sequence of independent random variables which are successively drawn from normal population. A test statistics based on modified likelihood ratio is proposed and its asymptotic null distribution is derived through the stochastic process representation. A small sample power comparison is made by Monte Carlo method.

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Noise-free Distributions Comparison of Bayesian Wavelet Threshold for Image Denoise

  • Choi, Ilsu;Rhee, Sung-Suk;Ahn, Yunkee
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.573-579
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    • 2001
  • Wavelet thresholding is a method for he reduction of noise in image. Wavelet coefficients of image are correlated in local characterization. Thee correlations also appear in he original pixel representation of the image, and they do not follow from the characterizations of the wavelet transform. In this paper, we compare noise-free distributions of Bayes approach to improve the classical threshold algorithm.

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