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Part 1: Document Description
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Citation |
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Title: |
ecg_biometric |
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Identification Number: |
doi:10.34820/FK2/BYSOCE |
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Distributor: |
Telkom University Dataverse |
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Date of Distribution: |
2022-04-01 |
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Version: |
1 |
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Bibliographic Citation: |
HADIYOSO, SUGONDO, 2022, "ecg_biometric", https://doi.org/10.34820/FK2/BYSOCE, Telkom University Dataverse, V1, UNF:6:7c58RzfcJoGhTU0icWRjFw== [fileUNF] |
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Citation |
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Title: |
ecg_biometric |
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Identification Number: |
doi:10.34820/FK2/BYSOCE |
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Authoring Entity: |
HADIYOSO, SUGONDO (Telkom University) |
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Distributor: |
Telkom University Dataverse |
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Access Authority: |
HADIYOSO, SUGONDO |
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Depositor: |
HADIYOSO, SUGONDO |
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Date of Deposit: |
2022-04-01 |
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Study Scope |
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Keywords: |
Engineering |
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Abstract: |
This dataset is ecg signal for biometric simulation. ECG signal was recorded using one lead ecg machine with sampling freq. 100Hz from 11 person. Data format .xlsx, separate by sheet every individual's ecg. To use the dataset please cite: 1. ECG based person authentication using empirical mode decomposition and discriminant analysis 2. One-Lead Electrocardiogram for Biometric Authentication using Time Series Analysis and Support Vector Machine 3. BIOMETRIC SYSTEMS BASED ON ECG USING ENSEMBLE EMPIRICAL MODE DECOMPOSITION AND VARIATIONAL MODE DECOMPOSITION Thank you |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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File Description--f4975 |
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File: ecg_data_person.tab |
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Notes: |
UNF:6:7c58RzfcJoGhTU0icWRjFw== |
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List of Variables: |
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Variables |
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f4975 Location: |
Variable Format: character Notes: UNF:6:7c58RzfcJoGhTU0icWRjFw== |