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- EMG Signal Decomposition Based on Wavelet Transform and ICA Method 应用小波变换和ICA方法的肌电信号分解
- EMG signal decomposition 肌电信号分解
- AIM: To detect surface electromyogram EMG signal accurately. 目的:准确地检测表面肌电信号。
- At last,the well output effect was gotten by the EMG signal of patients. 最后,通过病人的肌电信号,得到了良好的输出结果。
- Complexity Analysis of Surface EMG Signals. 表面肌电信号的复杂度特征研究。
- Parametric Autoregressive (AR) model is the traditional time-domain EMG signal analyzing method. 自回归(AR)参数模型是传统的肌电信号时域分析方法。
- Mallat. A theory for multiresolution signal decomposition:the wavelet representation[J].IEEE trans on Pattern Recog. and Machine Intel.1989,11:674-693. 张禀;陈刚;金以文.;基于金字塔正交小波分解的快速分形图像编码[J]
- To reduce these disadvanteages, the EMG signal is pre-disposed by wavelet de-noising theory. 这种方法很适合处理非特定人的肌电信号。
- The wavelet analysis can divide signal into different frequency bands and carry out inchoate signal decomposition and extracting. 小波分析能将信号划分到不同频段内,实现微弱故障信号的分离和提取。
- First, we discussed the physiologic principle, mechanism of EMG and the EMG signal model. 首先介绍了肌电产生的生理学基础及机理、肌电的信号模型。
- Surface EMG signal classification method based on wavelet transform is presented in this paper. 针对肌电信号的非平稳特性,采用小波变换方法对表面肌电信号进行分析。
- Method The concept of instantaneous median frequency surface EMG signal was discussed. 目的采用时频分析法分析表面肌电信号瞬时中值频率。
- Based on AGCD, an Optimized Initial-a-adaptive Gaussian chirplet signal decomposition algorithm (OI-AGCD) is proposed, and then be applied to ISAR imaging of maneuvering target. 该文在高斯包络线性调频基的自适应信号分解算法基础上,提出了基于优化初值选择高斯包络线性调频基自适应信号分解算法,并将其应用到ISAR成像中。
- Mallat S G.A theory for multiresolution signal decomposition:the wavelet representation[J].Pattern Analysis and Machine Intelligence,1989,11(7):674-693. 张建生李明轩.;脱粘界面超声检测信号的小波多分辨率分析与重构[J]
- The equations of SINS cosine matrix algorithm and its error angles are given and signal decomposition theory based on orthogonal wavelet is discussed in this paper. 给出了捷联惯导系统(SINS)解析粗对准时的捷联矩阵算法和相应的误差角公式,论述了基于正交小波的信号分解理论。
- EMG amplifier must have high gain, high input impedance, high CMRR and low noise because EMG signal itself is weak and interfered easily. 表面肌电信号本身幅值小、易受干扰,肌电信号放大器要求具有高放大倍数、高输入阻抗和高共模抑制比,同时又具有低噪声特性。
- Experiments show that using active electrode can improve ratio of signal and noise, reduce noise and detect surface EMG signal effectively. 实验表明,采用有源电极可以提高信噪比,减小噪声,有效地提取出表面肌电信号。
- The experiments showed that active electrode could be used to improve signal/noise ratio, reduce noise and detect surface EMG signal effectively. 实验表明 ,采用有源电极可以提高信噪比 ,减小噪声 ,有效地提取出表面肌电信号。
- The method of BP neural network improved by Levenberg-Marquardt algorithm in surface EMG signal classification is proposed. 提出用 Levenberg-Marquardt 算法改进 BP 神经网络识别表面肌电信号的方法。
- This paper introduces a method for feature extraction of surface EMG signal with fuzzy wavelet packet and classification with C4.5 decision tree. 提出了用模糊小波包提取表面肌电信号特征;并且用C4.;5决策树分类器对信号进行分类的方法。