Description: 实现信号的小波分解，绘制小波不同尺度下的信号分解图形，同时去除噪声，实现信号的小波重构-The realization of the wavelet decomposition of signals, mapping at different scales of wavelet signal decomposition graphics, while removing noise, the realization of the signal wavelet reconstruction Platform: |
Size: 8192 |
Author:wuqiang |
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Description: 脑电（EEG）是一种反映大脑活动的生物电信号，由于它具有很高的时变敏感性，在采集时极易受到外界的干扰。如眼球运动、眨眼、心电、肌电等都会给真实的脑电信号加入噪声（伪迹）。这些噪声给脑电信号的分析处理带来了很大的困难。从剔除EEG中的各种伪迹到去除噪声的效果评估研究者们都提出了很多方法。本文提出matlab除各种脑电信号伪伪迹减法- As a kind of physiological signals, the Electroencephalogram（EEG）represents the electrical activity of the brain. Because of its higher time-vary sensitivity, EEG is susceptible to many artifacts, such as eye-movements, blinks, cardiac signals, muscle noise. These noises in recording Electroencephalogram（EEG）pose a major embarrassment for EEG interpretation and disposal. A number of methods have been proposed to overcome this problem, ranging from the rejection of various artifacts to the effect estimate of removing artifacts. Platform: |
Size: 1024 |
Author:yangyangwang |
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Description: 1 Haar Wavelets
1.1 The Haar transform
1.2 Conservation and compaction of energy
1.3 Haar wavelets
1.4 Multiresolution analysis
1.5 Compression of audio signals
1.6 Removing noise from audio signals
1.7 Notes and references
2 Daub echies wavelets
2.1 The Daub4 wavelets
2.2 Conservation and compaction of energy
2.3 Other Daubechies wavelets
2.4 Compression of audio signals
2.5 Quantization, entropy, and compression
2.6 Denoising audio signals
2.7 Two-dimensional wavelet transforms
2.8 Compression of images
2.9 Fingerprint compression
2.10 Denoising images
2.11 Some topics in image processing
2.12 Notes and references
3 Frequency analysis
3.1 Discrete Fourier analysis
3.2 Definition of the DFT and its properties
3.3 Frequency description of wavelet analysis
3.4 Correlation and feature detection
3.5 Object detection in 2D images
3.6 Creating scaling signals and wavelets
3.7 Notes and references Platform: |
Size: 4108288 |
Author:Rakesh |
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Search - removing noise of signals