대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
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가중 정규화에 기반한 반복적 바이스펙트럼 추정과 신호복원

Iterative Bispectrum Estimation and Signal Recovery Based On Weighted Regularization

  • 임원배 (연세대학교 전기 컴퓨터공학과) ;
  • 허봉수 (연세대학교 전기 컴퓨터공학과) ;
  • 이학무 (연세대학교 전기 컴퓨터공학과) ;
  • 강문기 (연세대학교 전기 컴퓨터공학과)
  • Lim, Won-Bae (Dept of Electrical & Computer Engineering, Yonsei University) ;
  • Hur, Bong-Soo (Dept of Electrical & Computer Engineering, Yonsei University) ;
  • Lee, Hak-Moo (Dept of Electrical & Computer Engineering, Yonsei University) ;
  • Kang, Moon-Gi (Dept of Electrical & Computer Engineering, Yonsei University)
  • 발행 : 2000.05.25
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초록

바이스펙트럼은 신호 처리 및 영상 복원을 위한 적합한 특성을 강고 있고, 여러 응용분야에 적용될 수 있음에도 불구하고 설제로 적용된 결과가 문헌상으로 거의 나와 있지 않다 이는 표본이 부족하여 바이스펙트럼의 평균 연산이 어렵기 때문이다. 본 논문에서는, 참 바이스펙트럼을 표본 바이스펙트럼의 평균으로 정의한다. 그리고 표본 바이스펙트럼의 평균은 표본의 3중 상관함수의 푸리에 변환으로 나타낸다 표본 바이스펙트럼의 특성을 분석하고 일반화된 기중 정규화 이론을 적용하여 확률적으로 평균을 구하지 않고 참 바이스펙트럼을 추정하는 방법을 제안한다. 번지고 잡음이 낀 조건에서 제안한 알고리즘으로 바이스펙트럼을 추정 하고 이 결과가 신호의 복원에 유용함을 실험을 통해 증명한다.

While the bispectrum has desirable properties in itself and therefore has a lot of potential to be applied to signal and Image restoration. few real-world application results have appeared in literature The major problem with this IS the difficulty In realizing the expectation operator of the true bispectrum, due to the lack of realizations. In this paper, the true bispectrum is defined as the expectation of the sample bispectrum, which IS the Fourier representation of the triple correlation given one realization The characteristics of the sample bispectrum are analyzed and a way to obtain an estimate of the true bispectrum without stochastic expectation, using the generalized theory of weighted regularization is shown. The bispectrum estimated by the proposed algorithm is experimentally demonstrated to be useful for signal recovery under blurred noisy condition.

키워드

참고문헌

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