메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Liquan Zhao (Northeast Electric Power University) Ke Ma (Northeast Electric Power University)
저널정보
한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제16권 제6호
발행연도
2020.1
수록면
1,343 - 1,358 (16page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsityestimation is determined via maximum iterations. Different maximum iterations correspond to differentthresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variableweak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposedalgorithm uses the residual error value to control the weak threshold. When the residual value decreases, thethreshold value continuously increases, so that the atoms contained in the atomic set are closer to the realsparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved thegeneralized Jaccard coefficient in order to replace the inner product method that is used in the stagewisearithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace thejoint expectation for two variables based on the generalized Jaccard coefficient. The improved generalizedJaccard coefficient can be used to generate a more accurate calculation of the correlation between themeasurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selectingthe wrong atoms. We demonstrate using simulations that the proposed algorithm produces a betterreconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

목차

등록된 정보가 없습니다.

참고문헌 (17)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0