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Found 5 papers, 1 papers with code
Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation
Entropy measures are effective features for time series classification problems.
Heart Disease Detection using Quantum Computing and Partitioned Random Forest Methods
Compared to earlier works, the proposed HQRF achieved a maximum area under the curve (AUC) of 96. 43% and 97. 78% in predicting heart diseases using Cleveland and Statlog datasets, respectively with HQNN.
Novel techniques for improving NNetEn entropy calculation for short and noisy time series
Firstly, this work investigates different methods of filling the reservoir with time series (signal) elements.
A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks
Greater complexity in the time series leads to a higher classification accuracy and higher NNetEn values.
An improved LogNNet classifier for IoT application
In the age of neural networks and Internet of Things (IoT), the search for new neural network architectures capable of operating on devices with limited computing power and small memory size is becoming an urgent agenda.
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