Titlebook: EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction; Bita Mokhlesabadifarahani,Vinit Kumar

要旨

書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction影響因子(影響力)




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction影響因子(影響力)學(xué)科排名




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction網(wǎng)絡(luò)公開度




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction被引頻次




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction被引頻次學(xué)科排名




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction年度引用




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction年度引用學(xué)科排名




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction讀者反饋




書目名稱EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction讀者反饋學(xué)科排名

obstinate

EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction

insecticide

Book 2015s a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. The neuro-fuzzy system is trained with 70 percent of the recorded Electromyography (EMG) cut off window and then used for classification and modeling purposes. The neuro-fuzzy

Negotiate

貨物

Book 2015classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.

令人不快

2191-530X d EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.978-981-287-319-4978-981-287-320-0Series ISSN 2191-530X Series E-ISSN 2191-5318

令人不快

Strength

慟哭

Bita Mokhlesabadifarahani,Vinit Kumar GunjanIncludes supplementary material:

hereditary

SpringerBriefs in Applied Sciences and Technologyhttp://image.papertrans.cn/e/image/300430.jpg