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- W4221071933 abstract "Abstract This paper presents an estimation of missed samples recovery of Synthetic electrocardiography (ECG) signals by an ANFIS (Adaptive neuro-fuzzy inference system) method after designing the ANFIS model using FCM (Fuzzy C Means) clustering method. In MATLAB’s standard library for ANFIS, only least-square-estimation and the back-propagation algorithms are used for tuning membership functions and generation of fis (fuzzy inference system) file, but at current work, we have used the FCM method that shows better results. Root mean square error (difference of the reference input and the generated data by ANFIS) for the three synthetic data cases are: a. Train data: RMSE = 1.7112e-5 b. Test data: RMSE = 5.184e-3 c. All data: RMSE = 2.2663e-34" @default.
- W4221071933 created "2022-04-03" @default.
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- W4221071933 date "2022-03-23" @default.
- W4221071933 modified "2023-09-27" @default.
- W4221071933 title "Missing Samples Estimation of Synthetic ECG Signals by FCM-based Adaptive Neuro-Fuzzy Inference System (FCMANFIS)" @default.
- W4221071933 doi "https://doi.org/10.21203/rs.3.rs-1102921/v2" @default.
- W4221071933 hasPublicationYear "2022" @default.
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