• Title/Summary/Keyword: recursive

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A Study on Improvement in Digital Image Restoration by a Recursive Vector Processing (순환벡터처리에 의한 디지털 영상복원에 관한 연구)

  • 이대영;이윤현
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.8 no.3
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    • pp.105-112
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    • 1983
  • This paper discribes technique of the recursive restoration for the images degraded by linear space invariant blur and additive white Gaussian noise. The image is characterized statistically by tis mean and correlation function. An exponential autocorrelation function has been used to model neighborhood model. The vector model was used because of analytical simplicitly and capability to implement brightness correlation function. Base on the vector model, a two-dimensional discrete stochastic a 12 point neighborhood model for represeting images was developme and used the technique of moving window processing to restore blurred and noisy images without dimensionality increesing, It has been shown a 12 point neighborhood model was found to be more adequate than a 8 point pixel model to obtain optimum pixel estimated. If the image is highly correlated, it is necessary to use a large number of points in the neighborhood in order to have improvements in restoring image. It is believed that these result could be applied to a wide range of image processing problem. Because image processing thchniques normally required a 2-D linear filtering.

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Speech Enhancement Based on Improved Minima Controlled Recursive Averaging Incorporating GSAP (전역 음성 부재 확률 기반의 향상된 최소값 제어 재귀평균기법을 이용한 음성 향상 기법)

  • Song, Ji-Hyun;Bang, Dong-Hyeouck;Lee, Sang-Min
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.1
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    • pp.104-111
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    • 2012
  • In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA). From an examination for various noise environment, it is shown that the IMCRA has a fundamental drawback for the noise power estimate at the offset region of continuity speech signals. Espectially, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. To overcome the drawback, we apply the global speech absence probability (GSAP) conditioned on both a priori SNR and a posteriori SNR to the speech detection algorithm of IMCRA. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and a composite measure test, we show that the proposed algorithm yields better results compared to the conventional IMCRA-based scheme under various noise environments. In particular, in the case of babble 5 dB, the proposed method produced a remarkable improvement compared to the IMCRA ( PESQ = 0.026, composite measure = 0.029 ).

A Model of Recursive Hierarchical Nested Triangle for Convergence from Lower-layer Sibling Practices (하위 훈련 성과 융합을 위한 순환적 계층 재귀 모델)

  • Moon, Hyo-Jung
    • Journal of Digital Contents Society
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    • v.19 no.2
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    • pp.415-423
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    • 2018
  • In recent years, Computer-based learning, such as machine learning and deep learning in the computer field, is attracting attention. They start learning from the lowest level and propagate the result to the highest level to calculate the final result. Research literature has shown that systematic learning and growth can yield good results. However, systematic models based on systematic models are hard to find, compared to various and extensive research attempts. To this end, this paper proposes the first TNT(Transitive Nested Triangle)model, which is a growth and fusion model that can be used in various aspects. This model can be said to be a recursive model in which each function formed through geometric forms an organic hierarchical relationship, and the result is used again as they grow and converge to the top. That is, it is an analytical method called 'Horizontal Sibling Merges and Upward Convergence'. This model is applicable to various aspects. In this study, we focus on explaining the TNT model.

Prediction Models of P-Glycoprotein Substrates Using Simple 2D and 3D Descriptors by a Recursive Partitioning Approach

  • Joung, Jong-Young;Kim, Hyoung-Joon;Kim, Hwan-Mook;Ahn, Soon-Kil;Nam, Ky-Youb;No, Kyoung-Tai
    • Bulletin of the Korean Chemical Society
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    • v.33 no.4
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    • pp.1123-1127
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    • 2012
  • P-gp (P-glycoprotein) is a member of the ATP binding cassette (ABC) family of transporters. It transports many kinds of anticancer drugs out of the cell. It plays a major role as a cause of multidrug resistance (MDR). MDR function may be a cause of the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Hence classification of candidate drugs as substrates or nonsubstrate of the P-gp is important in drug development. Therefore to identify whether a compound is a P-gp substrate or not, in silico method is promising. Recursive Partitioning (RP) method was explored for prediction of P-gp substrate. A set of 261 compounds, including 146 substrates and 115 nonsubstrates of P-gp, was used to training and validation. Using molecular descriptors that we can interpret their own meaning, we have established two models for prediction of P-gp substrates. In the first model, we chose only 6 descriptors which have simple physical meaning. In the training set, the overall predictability of our model is 78.95%. In case of test set, overall predictability is 69.23%. Second model with 2D and 3D descriptors shows a little better predictability (overall predictability of training set is 79.29%, test set is 79.37%), the second model with 2D and 3D descriptors shows better discriminating power than first model with only 2D descriptors. This approach will be used to reduce the number of compounds required to be run in the P-gp efflux assay.

A RLS-based Convergent Algorithm for Driving Characteristic Classification for Personalized Autonomous Driving (자율주행 개인화를 위한 순환 최소자승 기반 융합형 주행특성 구분 알고리즘)

  • Oh, Kwang-Seok
    • Journal of the Korea Convergence Society
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    • v.8 no.9
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    • pp.285-292
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    • 2017
  • This paper describes a recursive least-squares based convergent algorithm for driving characteristic classification for personalized autonomous driving. Recently, various researches on autonomous driving technology have been conducted for level 4 fully autonomous driving. In order for commercialization of the autonomous vehicle, personalized autonomous driving is required to minimize passenger's insecureness to the autonomous vehicle. To address this problem. this study proposes mathematical model that represents driving characteristics and recursive least-squares based algorithm that can estimate the defined characteristics. The actual data of two drivers has been used to derive driving characteristics and the hypothesis testing method has been used to classify two drivers. It is shown that the proposed algorithms can derive driving characteristics and classify two drivers reasonably.

Fault Diameter of Recursive Circulant $G(2^{m},2^{k})$ (재귀원형군 $G(2^{m},2^{k})$의 고장 지름)

  • 김희철;정호영;박정흠
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.12
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    • pp.665-679
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    • 2002
  • The fault diameter of a graph G is the maximum of lengths of the shortest paths between all two vertices when there are $\chi$(G) - 1 or less faulty vertices, where $\chi$(G) is connectivity of G. In this paper, we analyze the fault diameter of recursive circulant $G(2^m,2^k)$ with $k{\geq}3$. Let $ dia_{m.k}$ denote the diameter of $G(2^m,2^k)$. We show that if $2{\leq}m,2{\leq}k, the fault diameter of $G(2{\leq}m,2{\leq}k)$ is equal to $2^m-2$, and if m=k+1, it is equal to $2^k-1$. It is also shown that for m>k+1, the fault diameter is equal to di a_$m{\neq}1$(mod 2k); otherwise, it is less than or equal to$dia_{m.k+2}$.

A Memory-based Reasoning Algorithm using Adaptive Recursive Partition Averaging Method (적응형 재귀 분할 평균법을 이용한 메모리기반 추론 알고리즘)

  • 이형일;최학윤
    • Journal of KIISE:Software and Applications
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    • v.31 no.4
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    • pp.478-487
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    • 2004
  • We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

Clock Synchronization for Multi-Static Radar Under Non-Line-of-Sight System Using Robust Least M-Estimation (로버스트한 최소 M-추정기법을 이용한 비가시선 상의 멀티스태틱 레이더 클락 동기 기술 연구)

  • Shin, Hyuk-Soo;Yeo, Kwang-Goo;Joeng, Myung-Deuk;Yang, Hoongee;Jung, Yongsik;Chung, Wonzoo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37C no.10
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    • pp.1004-1010
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    • 2012
  • In this paper, we propose the algorithm which considers applying recently proposed clock synchronization techniques with quite high accuracy in a few wireless sensor networks researches to time synchronization algorithm for multi-static radar system and especially overcomes the limitation of previous theory, cannot be applied between nodes in non-line of sight (NLOS). Proposed scheme estimates clock skew and clock offset using recursive robust least M-estimator with information of time stamp observations. And we improve the performance of algorithm by tracking and suppressing the time delays difference caused by NLOS system. Futhermore, this paper derive the mean square error (MSE) to present the performance of the proposed estimator and comparative analysis with previous methods.

A Component Composition Model based on Component Composition Specification (컴포넌트 결합 명세서에 기반한 컴포넌트 결합 모델)

  • Baek, Gyeong-Won;Park, Seong-Eun;Lee, Jeong-Tae;Ryu, Gi-Yeol
    • The KIPS Transactions:PartD
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    • v.8D no.6
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    • pp.723-734
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    • 2001
  • Today\\`s wide variety of component-based development environments supports the component framework that can be used only for the specific type of components. And many researches have shown that it is necessary for the component-based development environment to support recursive component composition, various kinds of component composition patterns and the multi-tier component architecture for the real benefits of software component composition. In this paper we propose the component composition specification which can not only specify the interaction contracts between components but also supports recursive component composition, and we also propose the component composition model based on this component composition specification. The proposed component composition specification can express the contractual properties that existing component specification techniques cannot specify, and it can be also used to implement the component architectures with multi-tier concept and the tool for component composition through supporting the various kinds of component composition patterns.

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An SQL Function for the Construction of Recursively Structured XML values from the Relational Data (관계 데이터로부터 재귀적 구조의 XML 값을 생성하는 SQL 함수)

  • Park, Sung-Chul;Park, Young-Chul
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.4
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    • pp.309-313
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    • 2009
  • SQL:2003 standard provides SQL/XML publishing functions to publish the result of an SQL query as XML values but it does not provide any SQL/XML publishing function that can publish the result of a recursive query as recursively structured XML values. Therefore, for the relational tuples which are connected directly or indirectly according to given conditions, to publish both the contents of them and the relationship among them as XML values with the use of appropriate SQL/XML publishing functions, we have to write a nested SQL query. Writing that query, however, is not easy provided that the depth of the connections is deep even if we know the depth of them and is not possible once the depth of the connections is not known in advance. In order to resolve that problem, we propose a new SQL function XMLNEST that can publish the result of a recursive query as recursively structured XML values.