• 제목/요약/키워드: dimension matrix

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DIMENSION MATRIX OF THE G-M FRACTAL

  • Kim, Tae-Sik
    • Journal of applied mathematics & informatics
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    • 제5권1호
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    • pp.13-22
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    • 1998
  • Fractals which represent many of the sets in various scien-tific fields as well as in nature is geometrically too complicate. Then we usually use Hausdorff dimension to estimate their geometrical proper-ties. But to explain the fractals from the hausdorff dimension induced by the Euclidan metric are not too sufficient. For example in digi-tal communication while encoding or decoding the fractal images we must consider not only their geometric sizes but also many other fac-tors such as colours densities and energies etc. So in this paper we define the dimension matrix of the sets by redefining the new metric.

Audio Fingerprint Retrieval Method Based on Feature Dimension Reduction and Feature Combination

  • Zhang, Qiu-yu;Xu, Fu-jiu;Bai, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.522-539
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    • 2021
  • In order to solve the problems of the existing audio fingerprint method when extracting audio fingerprints from long speech segments, such as too large fingerprint dimension, poor robustness, and low retrieval accuracy and efficiency, a robust audio fingerprint retrieval method based on feature dimension reduction and feature combination is proposed. Firstly, the Mel-frequency cepstral coefficient (MFCC) and linear prediction cepstrum coefficient (LPCC) of the original speech are extracted respectively, and the MFCC feature matrix and LPCC feature matrix are combined. Secondly, the feature dimension reduction method based on information entropy is used for column dimension reduction, and the feature matrix after dimension reduction is used for row dimension reduction based on energy feature dimension reduction method. Finally, the audio fingerprint is constructed by using the feature combination matrix after dimension reduction. When speech's user retrieval, the normalized Hamming distance algorithm is used for matching retrieval. Experiment results show that the proposed method has smaller audio fingerprint dimension and better robustness for long speech segments, and has higher retrieval efficiency while maintaining a higher recall rate and precision rate.

Free vibration analysis of asymmetric shear wall-frame buildings using modified finite element-transfer matrix method

  • Bozdogan, Kanat B.
    • Structural Engineering and Mechanics
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    • 제46권1호
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    • pp.1-17
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    • 2013
  • In this study, the modified finite element- transfer matrix methods are proposed for free vibration analysis of asymmetric structures, the bearing system of which consists of shear wall-frames. In the study, a multi-storey structure is divided into as many elements as the number of storeys and storey masses are influenced as separated at alignments of storeys. The shear walls and frames are assumed to be flexural and shear cantilever beam structures. The storey stiffness matrix is obtained by formulating the governing equation at the center of mass for the shear walls and the frames in the i.th floor. The system transfer matrix is constructed in the dimension of $6{\times}6$ by transforming the obtained stiffness matrix. Thus, the dimension, which is $12n{\times}12n$ in classical finite elements, is reduced to the dimension of $6{\times}6$. To study the suitability of the method, the results are assessed by solving two examples taken from the literature.

Comprehensive studies of Grassmann manifold optimization and sequential candidate set algorithm in a principal fitted component model

  • Chaeyoung, Lee;Jae Keun, Yoo
    • Communications for Statistical Applications and Methods
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    • 제29권6호
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    • pp.721-733
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    • 2022
  • In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

GIBBS PHENOMENON FOR WAVELETS IN HIGHER DIMENSION

  • SHIM HONG TAE;PARK CHIN HONG
    • Journal of applied mathematics & informatics
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    • 제17권1_2_3호
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    • pp.759-769
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    • 2005
  • We first discuss jump discontinuity in higher dimension, and then prove a local convergence theorem for wavelet approximations in higher dimension. We also redefine the concept of Gibbs phenomenon in higher dimension and show that wavelet expansion exhibits Gibbs phenomenon.

Adaptive data hiding scheme based on magic matrix of flexible dimension

  • Wu, Hua;Horng, Ji-Hwei;Chang, Chin-Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권9호
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    • pp.3348-3364
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    • 2021
  • Magic matrix-based data hiding schemes are applied to transmit secret information through open communication channels safely. With the development of various magic matrices, some higher dimensional magic matrices are proposed for improving the security level. However, with the limitation of computing resource and the requirement of real time processing, these higher dimensional magic matrix-based methods are not advantageous. Hence, a kind of data hiding scheme based on a single or a group of multi-dimensional flexible magic matrices is proposed in this paper, whose magic matrix can be expanded to higher dimensional ones with less computing resource. Furthermore, an adaptive mechanism is proposed to reduce the embedding distortion. Adapting to the secret data, the magic matrix with least distortion is chosen to embed the data and a marker bit is exploited to record the choice. Experimental results confirm that the proposed scheme hides data with high security and a better visual quality.

A Note on the Covariance Matrix of Order Statistics of Standard normal Observations

  • Lee, Hak-Myung
    • Communications for Statistical Applications and Methods
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    • 제7권1호
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    • pp.285-290
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    • 2000
  • We noted a property of a stationary distribution on the matrix C, which is the covariance matrix of order statistics of standard normal distribution That is the sup norm of th powers of C is ee' divided by its dimension. The matrix C can be taken as a transition probability matrix in an acyclic Markov chain.

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Aerosol optical depth prediction based on dimension reduction methods

  • Jungkyun Lee;Yaeji Lim
    • Communications for Statistical Applications and Methods
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    • 제31권5호
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    • pp.521-533
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    • 2024
  • As the concentration of fine dust has recently increased, numerous related studies are being conducted to address this issue. Aerosol optical depth (AOD) is a vital atmospheric parameter for measuring the optical properties of aerosols in the atmosphere, providing crucial information related to fine dust. In this paper, we apply three dimension reduction methods, nonnegative matrix factorization (NMF), empirical orthogonal functions (EOF) analysis and independent component analysis (ICA), to AOD data to analyze the patterns of fine dust in the East Asia region. Through a comparison of three dimension reduction methods, we observe that some patterns are observed in all three method, while some information are only extracted in a specific method. Additionally, we forecast AOD levels based on three methods, and compare the predictive performance of the three methodologies.

리터럴 스위치에 의한 다중제어 유니터리 게이트의 새로운 함수 임베딩 방법 (A New Function Embedding Method for the Multiple-Controlled Unitary Gate based on Literal Switch)

  • 박동영
    • 한국전자통신학회논문지
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    • 제12권1호
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    • pp.101-108
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    • 2017
  • 양자게이트 행렬은 치수가 r, 제어상태벡터 수가 n 및 표적상태벡터 수가 1인 경우에 $r^{n+1}{\times}r^{n+1}$ 차원 행렬이므로 n 증가에 따른 행렬 크기는 지수 함수적 증가 특성을 갖는다. 만약 제어상태벡터의 경우 수가 $2^n$이라면 $2^n-1$ 경우는 입력이 출력에 보전되는 단위행렬의 항등연산이고, 오직 한 개의 제어상태벡터 연산만이 표적상태벡터에 대한 유니터리 연산이다. 본 논문은 행렬차원 증가에 결정적 기여를 하는 $2^n-1$개의 단위행렬 연산을 한 동작의 산술멱승 연산으로 대체할 수 있는 새로운 함수 임베딩 방법을 제안한다. 제안한 함수 임베딩 방법은 다치 임계값을 갖는 2진 리터럴 스위치를 사용하므로 범용 하이브리드 MCU 게이트를 $r{\times}r$ 유니터리 행렬로 실현할 수 있다.

GORENSTEIN FLAT-COTORSION MODULES OVER FORMAL TRIANGULAR MATRIX RINGS

  • Wu, Dejun
    • 대한수학회보
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    • 제58권6호
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    • pp.1483-1494
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    • 2021
  • Let A and B be rings and U be a (B, A)-bimodule. If BU has finite flat dimension, UA has finite flat dimension and U ⊗A C is a cotorsion left B-module for any cotorsion left A-module C, then the Gorenstein flat-cotorsion modules over the formal triangular matrix ring $T=\(\array{A&0\\U&B}\)$ are explicitly described. As an application, it is proven that each Gorenstein flat-cotorsion left T-module is flat-cotorsion if and only if every Gorenstein flat-cotorsion left A-module and B-module is flat-cotorsion. In addition, Gorenstein flat-cotorsion dimensions over the formal triangular matrix ring T are studied.