• 제목/요약/키워드: self-mapping

검색결과 221건 처리시간 0.026초

클로펜스타인 테이퍼 구조의 초광대역 발룬 설계 (Design of Ultra-Wideband Klopfenstein Tapered Balun)

  • 이호상;유태훈;나완수
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2015년도 제46회 하계학술대회
    • /
    • pp.1273-1274
    • /
    • 2015
  • 본 논문에서는 주파수 무관(frequency independence) 특성을 갖는 자기상보 구조(self-complementary structure)로 된 안테나의 급전선로(feed line)로 사용할 수 있는 초광대역 발룬(ultra-wideband balun)을 제안하였다. 발룬을 설계하기 위해 클로펜스타인 테이퍼(Klopfenstein taper)를 사용하여 임피던스 프로파일(impedance profile)을 구하고 이를 평행 스트립 선로(parallel strip line) 구조로 구현하기 위해 등각사상방법(conformal mapping method)을 이용했다. 설계한 발룬을 직접 제작하여 측정한 결과, 대역폭은 반사손실 -10 dB를 기준으로 할 때 0.45~10.53 GHz까지 10.08 GHz로 나타나, UHF(ultra high frequency) 통신대역에서 UWB(ultra-wideband) 통신대역에 이르기까지 매우 넓은 주파수 범위에서 자기상보형 안테나의 입력 임피던스 $188{\Omega}$$50{\Omega}$의 특성 임피던스에 정합시킬 수 있음을 확인하였다.

  • PDF

PROVING UNIFIED COMMON FIXED POINT THEOREMS VIA COMMON PROPERTY (E-A) IN SYMMETRIC SPACES

  • Soliman, Ahmed Hussein;Imdad, Mohammad;Hasan, Mohammad
    • 대한수학회논문집
    • /
    • 제25권4호
    • /
    • pp.629-645
    • /
    • 2010
  • A metrical common fixed point theorem proved for a pair of self mappings due to Sastry and Murthy ([16]) is extended to symmetric spaces which in turn unifies certain fixed point theorems due to Pant ([13]) and Cho et al. ([4]) besides deriving some related results. Some illustrative examples to highlight the realized improvements are also furnished.

Human Face Recognition used Improved Back-Propagation (BP) Neural Network

  • Zhang, Ru-Yang;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
    • /
    • 제21권4호
    • /
    • pp.471-477
    • /
    • 2018
  • As an important key technology using on electronic devices, face recognition has become one of the hottest technology recently. The traditional BP Neural network has a strong ability of self-learning, adaptive and powerful non-linear mapping but it also has disadvantages such as slow convergence speed, easy to be traversed in the training process and easy to fall into local minimum points. So we come up with an algorithm based on BP neural network but also combined with the PCA algorithm and other methods such as the elastic gradient descent method which can improve the original network to try to improve the whole recognition efficiency and has the advantages of both PCA algorithm and BP neural network.

유한 셀룰러 오토마타 규칙 15에 대한 카테고리적 분석 (Categorical Analysis for Finite Cellular Automata Rule 15)

  • 박정희;이현열
    • 한국정보과학회논문지:시스템및이론
    • /
    • 제27권8호
    • /
    • pp.752-757
    • /
    • 2000
  • 두가지 상태값 (0, 1)과 서로 다른 네가지 경계조건을 갖는 1차원 셀룰러 오토마타 규칙 15의 상태전이그래프를 자기 재생시킬 수 있는 재귀식을 카테고리적 접근법으로 발견하였다. 카테고리적 접근법은 서로 다른 도메인을 갖는 오토마타들 간의 매핑을 가능케하므로 오토마타의 진화과정을 쉽게 표현할 수 있도록 한다.

  • PDF

Land Cover Clustering of NDVI-drived Phenological Features

  • Kim, Dong-Keun;Suh, Myoung-Seok;Park, Kyoung-Yoon
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
    • /
    • pp.201-206
    • /
    • 1998
  • In this paper, we have considered the method for clustering land cover types over the East Asia from AVHRR data. The feature vectors such that maximum NDVI, amplitude of NDVI, mean NDVI, and NDVI threshold are extracted from the 10-day composite by maximum value composite(MVC) for reducing the effect of cloud contaninations. To find the land cover clusters given by the feature vectors, we are adapted the self-organizing feature map(SOFM) clustering which is the mapping of an input vector space of n-dimensions into a one - or two-dimensional grid of output layer. The approach is to find first the clusters by the first layer SOFM and then merge several clusters of the first layer to a large cluster by the second layer SOFM. In experiments, we were used the 8-km AVHRR data for two years(1992-1993) over the East Asia.

  • PDF

동적 변화구조의 역전달 신경회로와 로보트의 역 기구학 해구현에의 응용 (A Dynamically Reconfiguring Backpropagation Neural Network and Its Application to the Inverse Kinematic Solution of Robot Manipulators)

  • 오세영;송재명
    • 대한전기학회논문지
    • /
    • 제39권9호
    • /
    • pp.985-996
    • /
    • 1990
  • An inverse kinematic solution of a robot manipulator using multilayer perceptrons is proposed. Neural networks allow the solution of some complex nonlinear equations such as the inverse kinematics of a robot manipulator without the need for its model. However, the back-propagation (BP) learning rule for multilayer perceptrons has the major limitation of being too slow in learning to be practical. In this paper, a new algorithm named Dynamically Reconfiguring BP is proposed to improve its learning speed. It uses a modified version of Kohonen's Self-Organizing Feature Map (SOFM) to partition the input space and for each input point, select a subset of the hidden processing elements or neurons. A subset of the original network results from these selected neuron which learns the desired mapping for this small input region. It is this selective property that accelerates convergence as well as enhances resolution. This network was used to learn the parity function and further, to solve the inverse kinematic problem of a robot manipulator. The results demonstrate faster learning than the BP network.

이동 로봇의 강인한 위치 추정을 통한 실내 SLAM (Robust Mobile-Robot Localization for Indoor SLAM)

  • 모세현;유동현;박종호;정길도
    • 제어로봇시스템학회논문지
    • /
    • 제22권4호
    • /
    • pp.301-306
    • /
    • 2016
  • This paper presents the results of a study for robust self-localization and indoor slam using external cameras (such as a CCTV) and odometry of mobile robot. First, a position of mobile robot was estimated by using maker and odometry. This data was then fused with camera data and odometry data using an extended kalman filter. Finally, indoor slam was realized by applying the proposed method. This was demonstrated in the actual experiment.

직관적 퍼지 거리공간에서 공통부동점 정리 및 예제 (Common fixed point theorem and example in intuitionistic fuzzy metric space)

  • 박종서;김선유
    • 한국지능시스템학회논문지
    • /
    • 제18권4호
    • /
    • pp.524-529
    • /
    • 2008
  • Park et.al.[10] defined the intuitionistic fuzzy metric space in which it is a little revised in Park[4], and Park et.a1.[7] proved a fixed point theorem of Banach for the contractive mapping of a complete intuitionistic fuzzy metric space. In this paper, we will establish common fixed point theorem for four self maps in intuitionistic fuzzy metric space. These results have been used to obtain translation and generalization of Grabiec's contraction principle.

대각귀환 신경망을 이용한 비선형 적응 제어 (Adaptive Control of the Nonlinear Systems Using Diagonal Recurrent Neural Networks)

  • 류동완;이영석;서보혁
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1996년도 하계학술대회 논문집 B
    • /
    • pp.939-942
    • /
    • 1996
  • This paper presents a stable learning algorithm for diagonal recurrent neural network(DRNN). DRNN is applied to a problem of controlling nonlinear dynamical systems. A architecture of DRNN is a modified model of the Recurrent Neural Network(RNN) with one hidden layer, and the hidden layer is comprised of self-recurrent neurons. DRNN has considerably fewer weights than RNN. Since there is no interlinks amongs in the hidden layer. DRNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. To guarantee convergence and for faster learning, an adaptive learning rate is developed by using Lyapunov function. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed algorithm is demonstrated by computer simulation.

  • PDF

NORM OF THE COMPOSITION OPERATOR MAPPING BLOCH SPACE INTO HARDY OR BERGMAN SPACE

  • Kwon, Ern-Gun;Lee, Jin-Kee
    • 대한수학회논문집
    • /
    • 제18권4호
    • /
    • pp.653-659
    • /
    • 2003
  • Let $1{\;}\leq{\;}p{\;}\infty{\;}and{\;}{\alpha}{\;}>{\;}-1$. If f is a holomorphic self-map of the open unit disc U of C with f(0) = 0, then the quantity $\int_U\;\{\frac{$\mid$f'(z)$\mid$}{1\;-\;$\mid$f(z)$\mid$^2}\}^p\;(1\;-\;$\mid$z$\mid$)^{\alpha+p}dxdy$ is equivalent to the operator norm of the composition operator $C_f{\;}:{\;}B{\;}\rightarrow{\;}A^{p,{\alpha}$ defined by $C_fh{\;}={\;}h{\;}\circ{\;}f{\;}-{\;}h(0)$, where B and $A^{p,{\alpha}$ are the Bloch space and the weighted Bergman space on U respectively.