Fixed-point FPGA Implementation of ECG Classification using Artificial Neural Network
Author:
Affiliation:
1. Izmir University of Economics,Faculty of Engineering,Izmir,Turkey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9960140/9959864/09960216.pdf?arnumber=9960216
Reference14 articles.
1. FPGA Implementation of Artificial Neural Network (ANN) for ECG Signal Classification
2. Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks
3. PhysioBank, PhysioToolkit, and PhysioNet
4. A Low-Latency, Low-Power FPGA Implementation of ECG Signal Characterization Using Hermite Polynomials
5. Automatic Arrhythmia Detection Based on the Probabilistic Neural Network with FPGA Implementation
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1. FPGA Accelerated Convolutional Neural Network for Detection of Cardiac Arrhythmia;2024 IEEE 4th International Conference on VLSI Systems, Architecture, Technology and Applications (VLSI SATA);2024-05-17
2. Harnessing FPGA Technology to Classify ECG Signal with Neural Networks;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09
3. Development of a Device on FPGA to Implement the Base Operation of Neural-like Data Encryption Using Polynomials;2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT);2023-10-19
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