• 제목/요약/키워드: invariance

검색결과 357건 처리시간 0.028초

Molecular Spinless Energies of the Modified Rosen-Morse Potential Energy Model

  • Jia, Chun-Sheng;Peng, Xiao-Long;He, Su
    • Bulletin of the Korean Chemical Society
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    • 제35권9호
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    • pp.2699-2703
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    • 2014
  • We solve the Klein-Gordon equation with the modified Rosen-Morse potential energy model. The bound state energy equation has been obtained by using the supersymmetric shape invariance approach. The relativistic vibrational transition frequencies for the $6^1{\Pi}_u$ state of the $^7Li_2$ molecule have been computed by using the modified Rosen-Morse potential model. The calculated relativistic vibrational transition frequencies are in good agreement with the experimental RKR values.

Carrier Frequency Offset Estimation Using ESPRIT for the Interleaved OFDMA Uplink Systems

  • Lee, Jung-Hoon;Lee, Sung-Eun;Hong, Dae-Sik
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.175-178
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    • 2005
  • In this paper, a carrier frequency offset (CFO) estimator is proposed for the interleaved OFDMA uplink systems. It is based on the estimation of signal parameters via rotational invariance technique (ESPRIT). Compared with the Cao's estimator, the proposed estimator has low computational complexity. Simulation results demonstrate that the proposed estimator performs better than Cao's estimator at the relatively low SNR region. Hence, the proposed estimator is more applicable to the practical environments than the Cao’s estimator.

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Deep Convolution Neural Networks in Computer Vision: a Review

  • Yoo, Hyeon-Joong
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권1호
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    • pp.35-43
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    • 2015
  • Over the past couple of years, tremendous progress has been made in applying deep learning (DL) techniques to computer vision. Especially, deep convolutional neural networks (DCNNs) have achieved state-of-the-art performance on standard recognition datasets and tasks such as ImageNet Large-Scale Visual Recognition Challenge (ILSVRC). Among them, GoogLeNet network which is a radically redesigned DCNN based on the Hebbian principle and scale invariance set the new state of the art for classification and detection in the ILSVRC 2014. Since there exist various deep learning techniques, this review paper is focusing on techniques directly related to DCNNs, especially those needed to understand the architecture and techniques employed in GoogLeNet network.

누적 유사도 변환을 이용한 물체 추적 (Moving Object Tracking using Cumulative Similarity Transform)

  • Choo, Moon-Won
    • 한국콘텐츠학회논문지
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    • 제3권1호
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    • pp.58-63
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    • 2003
  • 동영상에서의 물체추적은 각 프레임간의 시공간적 정보의 대응성을 추적함으로써 이루어질 수 있다. 시공간적 대응성을 결정함에 있어 각 프레임의 color invariant 속성을 이용하여 각 프레임의 물체 위치를 예측하고, 추출된 물체 블록의 누적 유사도 변환을 적용한 수치를 이용하여 프레임간의 물체 대응성을 결정함으로써 물체를 추적하는 방법론을 제시한다. 실험결과를 통하여 이러한 방법의 적용 적절성을 검증하였다.

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타르스키의 논리상항의 정의에 대한 연구

  • 최병일
    • 논리연구
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    • 제3권
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    • pp.95-113
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    • 2000
  • 타르스키는 최근 발표된 그의 유고에서 흥미 있는 논리상항의 정의를 제공하였다. 그의 정의는 그가 1927년이래 린덴바움과 함께 연구하였고, 1935년에 강연으로 발표하였던 메타 논리적 탐구의 결과들에 근거하는 것으로서, 1966년과 1973년의 강연들에서 제공하였던 '논리적 개념들'(logical notions)의 정의에 바탕을 둔 것이었다. 타르스키의 논리상항의 정의는 역사적으로는 클라인의 에어랑겐 프로그램(Erlangen Programme)의 논리학에 대한 적용이라 할 수 있는 것으로서, 마우트너의 유사한 시도와 함께 주목할 만한 가치가 있다. 또한 그의 정의는 논리상항을 논리적 형식의 개념에 의존하지 않고, 보다 중립적인 '모든 변환에 있어 불변적임'(invariance under all transformations)이라는 개념을 사용하고 있다는 점에서도 흥미있는 시도로서 여겨질 수 있다. 본 논문에서는 타르스키의 논리상항의 정의와 그 확장에 대하여 논의한 뒤, 몇 가지 비판적인 논점을 제공하고자 한다. 특히 타르스키의 정의가 과연 중립적이고 순환적이지 않은가 하는 문제에 대한 논의를 통하여 논리상항의 정의에 대한 새로운 관점을 확보하고자 한다.

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ON SURJECTIVITY OF m-ACCRETIVE OPERATORS IN BANACH SPACES

  • Han, Song-Ho;Kim, Myeong-Hwan;Park, Jong An.
    • 대한수학회보
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    • 제26권2호
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    • pp.203-209
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    • 1989
  • Recently many authors [2,3,5,6] proved the existence of zeros of accretive operators and estimated the range of m-accretive operators or compact perturbations of m-accretive operators more sharply. Their results could be obtained from differential equations in Banach spaces or iteration methods or Leray-Schauder degree theory. On the other hand Kirk and Schonberg [9] used the domain invariance theorem of Deimling [3] to prove some general minimum principles for continuous accretive operators. Kirk and Schonberg [10] also obtained the range of m-accretive operators (multi-valued and without any continuity assumption) and the implications of an equivalent boundary conditions. Their fundamental tool of proofs is based on a precise analysis of the orbit of resolvents of m-accretive operator at a specified point in its domain. In this paper we obtain a sufficient condition for m-accretive operators to have a zero. From this we derive Theorem 1 of Kirk and Schonberg [10] and some results of Morales [12, 13] and Torrejon[15]. And we further generalize Theorem 5 of Browder [1] by using Theorem 3 of Kirk and Schonberg [10].

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Secure Biometric Hashing by Random Fusion of Global and Local Features

  • Ou, Yang;Rhee, Kyung-Hyune
    • 한국멀티미디어학회논문지
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    • 제13권6호
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    • pp.875-883
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    • 2010
  • In this paper, we present a secure biometric hashing scheme for face recognition by random fusion of global and local features. The Fourier-Mellin transform and Radon transform are adopted respectively to form specialized representation of global and local features, due to their invariance to geometric operations. The final biometric hash is securely generated by random weighting sum of both feature sets. A fourfold key is involved in our algorithm to ensure the security and privacy of biometric templates. The proposed biometric hash can be revocable and replaced by using a new key. Moreover, the attacker cannot obtain any information about the original biometric template without knowing the secret key. The experimental results confirm that our scheme has a satisfactory accuracy performance in terms of EER.

Utkin 정리의 다입력 불확실 선형 시스템에 대한 증명 (A Poof of Utkin's Theorem for a MI Uncertain Linear Case)

  • 이정훈
    • 전기학회논문지
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    • 제59권9호
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    • pp.1680-1685
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    • 2010
  • In this note, a proof of Utkin's theorem is presented for a MI(Multi Input) uncertain linear case. The invariance theorem with respect to the two transformation methods so called the two diagonalization methods are proved clearly and comparatively for MI uncertain linear systems. With respect to the sliding surface transformation and the control input transformation, the equation of the sliding mode i.e., the sliding surface is invariant. Both control inputs have the same gains. By means of the two transformation methods the same results can be obtained. Through an illustrative example and simulation study, the usefulness of the main results is verified.

Robust and Optimal Attitude Control Law Design for Spacecraft with Inertia Uncertainties

  • Park, Yon-Mook;Tahk, Min-Jea
    • International Journal of Aeronautical and Space Sciences
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    • 제3권2호
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    • pp.1-12
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    • 2002
  • This paper considers the robust and optimal three-axis attitude stabilization of rigid spacecraft with inertia uncertainties. The attitude motion of rigid spacecraft described in terms of either the Cayley-Rodrigues parameters or the Modified Rodrigues parameters is considered. A class of robust nonlinear control laws with relaxed feedback gain structures is proposed for attitude stabilization of rigid spacecraft with inertia uncertainties. Global asymptotic stability of the proposed control laws is shown by using the LaSalle Invariance Principle. The optimality properties of the proposed control laws are also investigated by using the Hamilton-Jacobi theory. A numerical example is given to illustrate the theoretical results presented in this paper.

THE INVARIANCE PRINCIPLE FOR LINEARLY POSITIVE QUADRANT DEPENDENT SEQUENCES

  • Kim, Tae-Sung;Han, Kwang-Hee
    • 대한수학회논문집
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    • 제9권4호
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    • pp.951-959
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    • 1994
  • A sequence ${X_j : j \geq 1}$ of random variables is said to be pairwise positive quadrant dependent (pairwise PQD) if for any real $r-i,r_j$ and $i \neq j$ $$ P{X_i > r_i,X_j > r_j} \geq P{X_i > r_i}P{X_j > r_j} $$ (see [8]) and a sequence ${X_j : j \geq 1}$ of random variables is said to be associated if for any finite collection ${X_{i(1)},...,X_{j(n)}}$ and any real coordinatewise nondecreasing functions f,g on $R^n$ $$ Cov(f(X_{i(1)},...,X_{j(n)}),g(X_{j(1)},...,X_{j(n)})) \geq 0, $$ whenever the covariance is defined (see [6]). Instead of association Cox and Grimmett's [4] original central limit theorem requires only that positively linear combination of random variables are PQD (cf. Theorem $A^*$).

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