• Title/Summary/Keyword: AMP(Approximate Message Passing)

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Introduction and Performance Analysis of Approximate Message Passing (AMP) for Compressed Sensing Signal Recovery (압축 센싱 신호 복구를 위한 AMP(Approximate Message Passing) 알고리즘 소개 및 성능 분석)

  • Baek, Hyeong-Ho;Kang, Jae-Wook;Kim, Ki-Sun;Lee, Heung-No
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.11
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    • pp.1029-1043
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    • 2013
  • We introduce Approximate Message Passing (AMP) algorithm which is one of the efficient recovery algorithms in Compressive Sensing (CS) area. Recently, AMP algorithm has gained a lot of attention due to its good performance and yet simple structure. This paper provides not only a understanding of the AMP algorithm but its relationship with a classical (Sum-Product) Message Passing (MP) algorithm. Numerical experiments show that the AMP algorithm outperforms the classical MP algorithms in terms of time and phase transition.

Novel Transmission System of 3D Broadcasting Signals using Compressed Sensing (압축 센싱을 이용한 3D 방송 신호 전송 시스템)

  • Lee, Sun Yui;Cha, Jae Sang;Park, Gooman;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.8 no.4
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    • pp.130-134
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    • 2013
  • This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduce the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept was described. Recently proposed CS algorithm AMP(Approximate Message Passing) and CoSaMP(Compressive Sampling Matched Pursuit) was described. Image data that compressed and restored by these algorithm was compared. Calculation time of the algorithm having a low complexity is determined.

Sampling Techniques for Wireless Data Broadcast in Communication (통신에서의 무선 데이터 방송을 위한 샘플링 기법)

  • Lee, Sun Yui;Park, Gooman;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.10 no.3
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    • pp.57-61
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    • 2015
  • This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept was described. CS algorithm SS-CoSaMP(Single-Space Compressive Sampling Matched Pursuit) and AMP(Approximate Message Passing) was described. Image data compressed and restored by these algorithm was compared. Calculation time of the algorithm having a low complexity is determined.

Compressed Sensing Techniques for Video Transmission of Multi-Copter (멀티콥터 영상 전송을 위한 압축 센싱 기법)

  • Jung, Kuk Hyun;Lee, Sun Yui;Lee, Sang Hwa;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.9 no.2
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    • pp.63-68
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    • 2014
  • This paper proposed a novel compressed sensing (CS) technique for an efficient video transmission of multi-copter. The proposed scheme is focused on reduction of the amount of data based on CS technology. First, we describe basic principle of Spectrum sensing. And then we compare AMP(Approximate Message Passing) with CoSaMP(Compressive Sampling Matched Pursuit) through mathematical analysis and simulation results. They are evaluated in terms of calculation time and complexity, then the promising algorithm is suggestd for multicopter operation. The result of experiment in this paper shows that AMP algorithm is more efficient than CoSaMP algorithm when it comes to calculation time and image error probability.

Novel Compressed Sensing Techniques for Realistic Image (실감 영상을 위한 압축 센싱 기법)

  • Lee, Sun Yui;Jung, Kuk Hyun;Kim, Jin Young;Park, Gooman
    • Journal of Satellite, Information and Communications
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    • v.9 no.3
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    • pp.59-63
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    • 2014
  • This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept were described. Recently proposed CS algorithm AMP(Approximate Message Passing) and CoSaMP(Compressive Sampling Matched Pursuit) were described. This paper compared an accuracy between two algorithms and a calculation time that image data compressed and restored by these algorithms. As result determines a low complexity algorithm for 3D broadcast system.