The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
준주기적 신호는 주기와 진폭 변화가 있는 주기적인 신호입니다. 심전도(ECG)를 포함한 여러 생리학적 신호는 준주기적으로 처리될 수 있습니다. 벡터 양자화(VQ)는 신호 압축을 위한 가치 있고 보편적인 도구입니다. 그러나 VQ를 사용하여 준주기 신호를 압축하면 몇 가지 문제가 발생합니다. 첫째, 사전 훈련된 코드북은 신호 변화에 거의 적응하지 못하여 재구성된 신호의 품질 제어가 불가능합니다. 둘째, 신호의 주기성으로 인해 많은 코드벡터가 높은 상관관계를 갖는 코드북에서 데이터 중복이 발생합니다. 이 두 가지 문제는 제안된 BS(bar-shape) 코드북 구조를 기반으로 하는 CRVQ(codebook replenishment VQ) 방식에 의해 해결된다. CRVQ에서는 신호 변화에 따라 코드벡터를 온라인으로 업데이트할 수 있으며 재구성된 신호의 품질을 지정할 수 있습니다. BS 코드북 구조를 사용하면 코드북 중복성이 크게 줄어들고 코드북 저장 공간이 크게 절약됩니다. 더욱이 가변 차원(VD) 코드벡터를 사용하여 왜곡 제약이 적용되는 코딩 비트율을 최소화할 수 있습니다. VD-CRVQ의 이론적 근거와 구현 방안을 제시합니다. MIT/BIH 부정맥 데이터베이스의 ECG 데이터를 테스트한 결과 다른 VQ 압축 방법을 사용한 결과보다 훨씬 더 나은 결과를 얻었습니다.
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Shaou-Gang MIAOU, "Compression of Physiological Quasi-Periodic Signals Using Optimal Codebook Replenishment Vector Quantization with Distortion Constraint" in IEICE TRANSACTIONS on Information,
vol. E85-D, no. 8, pp. 1325-1333, August 2002, doi: .
Abstract: A quasi-periodic signal is a periodic signal with period and amplitude variations. Several physiological signals, including the electrocardiogram (ECG), can be treated as quasi-periodic. Vector quantization (VQ) is a valuable and universal tool for signal compression. However, compressing quasi-periodic signals using VQ presents several problems. First, a pre-trained codebook has little adaptation to signal variations, resulting in no quality control of reconstructed signals. Secondly, the periodicity of the signal causes data redundancy in the codebook, where many codevectors are highly correlated. These two problems are solved by the proposed codebook replenishment VQ (CRVQ) scheme based on a bar-shaped (BS) codebook structure. In the CRVQ, codevectors can be updated online according to signal variations, and the quality of reconstructed signals can be specified. With the BS codebook structure, the codebook redundancy is reduced significantly and great codebook storage space is saved; moreover variable-dimension (VD) codevectors can be used to minimize the coding bit rate subject to a distortion constraint. The theoretic rationale and implementation scheme of the VD-CRVQ is given. The ECG data from the MIT/BIH arrhythmic database are tested, and the result is substantially better than that of using other VQ compression methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/e85-d_8_1325/_p
부
@ARTICLE{e85-d_8_1325,
author={Shaou-Gang MIAOU, },
journal={IEICE TRANSACTIONS on Information},
title={Compression of Physiological Quasi-Periodic Signals Using Optimal Codebook Replenishment Vector Quantization with Distortion Constraint},
year={2002},
volume={E85-D},
number={8},
pages={1325-1333},
abstract={A quasi-periodic signal is a periodic signal with period and amplitude variations. Several physiological signals, including the electrocardiogram (ECG), can be treated as quasi-periodic. Vector quantization (VQ) is a valuable and universal tool for signal compression. However, compressing quasi-periodic signals using VQ presents several problems. First, a pre-trained codebook has little adaptation to signal variations, resulting in no quality control of reconstructed signals. Secondly, the periodicity of the signal causes data redundancy in the codebook, where many codevectors are highly correlated. These two problems are solved by the proposed codebook replenishment VQ (CRVQ) scheme based on a bar-shaped (BS) codebook structure. In the CRVQ, codevectors can be updated online according to signal variations, and the quality of reconstructed signals can be specified. With the BS codebook structure, the codebook redundancy is reduced significantly and great codebook storage space is saved; moreover variable-dimension (VD) codevectors can be used to minimize the coding bit rate subject to a distortion constraint. The theoretic rationale and implementation scheme of the VD-CRVQ is given. The ECG data from the MIT/BIH arrhythmic database are tested, and the result is substantially better than that of using other VQ compression methods.},
keywords={},
doi={},
ISSN={},
month={August},}
부
TY - JOUR
TI - Compression of Physiological Quasi-Periodic Signals Using Optimal Codebook Replenishment Vector Quantization with Distortion Constraint
T2 - IEICE TRANSACTIONS on Information
SP - 1325
EP - 1333
AU - Shaou-Gang MIAOU
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E85-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2002
AB - A quasi-periodic signal is a periodic signal with period and amplitude variations. Several physiological signals, including the electrocardiogram (ECG), can be treated as quasi-periodic. Vector quantization (VQ) is a valuable and universal tool for signal compression. However, compressing quasi-periodic signals using VQ presents several problems. First, a pre-trained codebook has little adaptation to signal variations, resulting in no quality control of reconstructed signals. Secondly, the periodicity of the signal causes data redundancy in the codebook, where many codevectors are highly correlated. These two problems are solved by the proposed codebook replenishment VQ (CRVQ) scheme based on a bar-shaped (BS) codebook structure. In the CRVQ, codevectors can be updated online according to signal variations, and the quality of reconstructed signals can be specified. With the BS codebook structure, the codebook redundancy is reduced significantly and great codebook storage space is saved; moreover variable-dimension (VD) codevectors can be used to minimize the coding bit rate subject to a distortion constraint. The theoretic rationale and implementation scheme of the VD-CRVQ is given. The ECG data from the MIT/BIH arrhythmic database are tested, and the result is substantially better than that of using other VQ compression methods.
ER -