The use of adaptive segmentation to noise reduction and compression of non-stationary signals

机译：使用自适应分段来减少和压缩非平稳信号

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

Real life signals are mostly non-stationary, and the most interesting information they carry is in their non- stationary characteristics (the beginning or the end of an event, drifts, transient faults). In this work, we are extending Saito's algorithm for noise reduction and signal compression to non-stationary signals. This extension is achieved by adaptively segmenting the non-stationary signal in such a way that each segment of the signal behaves like a stationary signal. Our results show that this adaptive segmentation improves the noise reduction and the compression of the signal.

机译：现实生活中的信号大多是非平稳的，它们所携带的最有趣的信息是其非平稳特征（事件的开始或结束，漂移，瞬态故障）。在这项工作中，我们将Saito的降噪和信号压缩算法扩展到非平稳信号。这种扩展是通过对非平稳信号进行自适应分段来实现的，以使信号的每个段都表现得像静止信号一样。我们的结果表明，这种自适应分段可提高降噪效果和信号压缩率。

著录项

来源
《The 2nd International Workshop on Artificial Intelligence and Mathematical Methods in Pavement and Geomechanical Systems, Aug 11-12, 2000, Newark, Delaware, USA》|2000年|p.67-74|共8页
会议地点 Newark DE(US)
作者
Jean H.Andrian;
展开▼
作者单位

Department of Electrical Computer Engineering, Florida International University, Miami, Fla., USA;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类公路运输;
关键词

相似文献

外文文献
中文文献
专利

1. FPGA implementation of adaptive segmentation for non-stationary biomedical signals [J] . Circuits, Devices & Systems, IET . 2010,第3期

机译：非平稳生物医学信号自适应分段的FPGA实现
2. A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise, minimum mean square variance criterion and least mean square adaptive filter [J] . Yu-xing Li, Long Wang 兵工学报（英文版） . 2020,第003期
3. Speech Recognition System using Wavelet Analysis (Reduction of Non-stationary Noise and Database Compression) [J] . Ping Ma, Takuya Yoshimura and Kohei Suzuki 日本機械学会論文集. C編 . 2001,第653期

机译：小波分析的语音识别系统（减少非平稳噪声和数据库压缩）
4. The use of adaptive segmentation to noise reduction and compression of non-stationary signals [C] . Jean H.Andrian International workshop on artificial intelligence and mathematical methods in pavement and geomechanical systems . 2000

机译：使用自适应分割对非静止信号的降噪和压缩
5. Application of wavelet transforms for data compression, noise reduction and interpretation of digital seismic signals. [D] . Nefzaoui, Azza. 2002

机译：小波变换在数据压缩，降噪和数字地震信号解释中的应用。
6. An intelligent approach for variable size segmentation of non-stationary signals [O] . Hamed Azami, Hamid Hassanpour, Javier Escudero, 2015

机译：一种用于非平稳信号的可变大小分割的智能方法
7. Behavior of the adaptive algorithm for non-stationary noise signal: Difference between theoretical formulation and the practical implementation [O] . Yoko Takenouchi, Hisaharu Suzuki, Akira Omoto 2004

机译：非静止噪声信号自适应算法的行为：理论配方与实际实现之间的差异
8. Application of Adaptive Noise Cancellation to Noise Reduction in Audio Signals. [R] . Pulsipher, D. C. 1979

机译：自适应噪声消除在音频信号降噪中的应用。

The use of adaptive segmentation to noise reduction and compression of non-stationary signals

摘要

著录项

相似文献

相关主题

期刊订阅