This paper presents continuous heartbeat monitoring using evolvable block-based neural networks (BbNNs). An evolutionary algorithm is used to optimize the ...
This paper presents continuous heartbeat monitoring using evolvable block-based neural networks. The structure and weights of a BbNN are evolved for a subject.
In this work the implementation of an end-to-end NILM system is presented, which comprises a custom high frequency meter and neural-network based ... [Show full ...
This paper presents continuous heartbeat monitoring using evolvable block-based neural networks (BbNNs). An evolutionary algorithm is used to optimize the ...
The goal of this project is to design and implement block-based neural networks (BbNNs), an evolvable neural network model suitable for dynamic environments. A ...
Jun 18, 2024 · This study investigates advanced deep learning models, including LSTM, and transformer-based architectures, for predicting heart rate time series from the MIT- ...
This paper presents evolvable BbNNs for the classification of abnormal heartbeat patterns from the ECG signal. The internal structure and associated weights of ...
This paper presents a design of block-based neural networks (BbNNs) on FPGAs capable of dynamic adaptation and online training.
Time series prediction with evolvable block-based neural networks ...
www.semanticscholar.org › paper
This paper presents continuous heartbeat monitoring using evolvable block-based neural networks (BbNNs). An evolutionary algorithm is used to optimize the ...
This paper proposes a CNN-jSO approach for the prediction of heart (cardiac) diseases, in which the jSO optimization algorithm is employed to tune those CNN ...