针对传统心音去噪算法对强噪声下心音信号去噪时,易将部分心音信号视为噪声成分去除,导致有用心音信号能量损失。利用奇异谱分析方法的主成分分析特性,提出多级奇异值分解(Multi-stage Singular Value Decomposition,MS-SVD)算法用于提...针对传统心音去噪算法对强噪声下心音信号去噪时,易将部分心音信号视为噪声成分去除,导致有用心音信号能量损失。利用奇异谱分析方法的主成分分析特性,提出多级奇异值分解(Multi-stage Singular Value Decomposition,MS-SVD)算法用于提取心音信号的主分量(Principal Components,PC)信息;采用小波包(Wavelet Packet,WP)分析算法对提取的心音信号进行分解,并对分解所得低频系数进行自适应阈值处理,去除低频噪声;利用小波包多分辨率特性提取高频心音。实验结果表明,该算法能明显改善心音去噪性能指标信噪比(SNR)、信噪比增益(SNRG)及根均方误差(RMSE),且在不同噪声水平下的去噪性能优于传统心音去噪算法。此改进算法既能有效去除心音中噪声成分,亦能保留心音信号细节特征。展开更多
为对变压器有载分接开关机械故障进行诊断,提出一种结合奇异值分解SVD(singular value decompo-sition)消噪与小波包WP(wavelet packet)消噪的信号特征提取方法。首先对信号进行小波包消噪,然后进行SVD二次消噪,将消噪信号进行经验模态...为对变压器有载分接开关机械故障进行诊断,提出一种结合奇异值分解SVD(singular value decompo-sition)消噪与小波包WP(wavelet packet)消噪的信号特征提取方法。首先对信号进行小波包消噪,然后进行SVD二次消噪,将消噪信号进行经验模态分解EMD(empirical mode decomposition),对得出的各阶固有模态分量进行希尔伯特-黄变换HHT(Hilbert-Huang transform)。数值仿真表明基于WP_SVD降噪的信号特征提取比小波包或SVD单独降噪的信号特征提取方法有效,并成功地将该方法应用到分接开关实际振动信号分析中。展开更多
As an elegant generalization of wavelet transform, wavelet packet （WP） provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition ...As an elegant generalization of wavelet transform, wavelet packet （WP） provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quanUzation scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.展开更多
基金the Major State Basic Research Development Program(973 Program)(Grant No.2004CB318005)
文摘As an elegant generalization of wavelet transform, wavelet packet （WP） provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quanUzation scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.
