37 citations · 82 across the 5 of their papers we have counts for
5 papers
Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation
Andrei Velichko, Maksim Belyaev, Yuriy Izotov +2
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. Howev…
Heart Disease Detection using Quantum Computing and Partitioned Random Forest Methods
Hanif Heidari, Gerhard Hellstern, Murugappan Murugappan
Heart disease morbidity and mortality rates are increasing, which has a negative impact on public health and the global economy. Early detection of heart disease reduces the incide…
Novel techniques for improving NNetEn entropy calculation for short and noisy time series
Hanif Heidari, Andrei Velichko, Murugappan Murugappan +1
Entropy is a fundamental concept in the field of information theory. During measurement, conventional entropy measures are susceptible to length and amplitude changes in time serie…
A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks
Andrei Velichko, Hanif Heidari
Measuring the predictability and complexity of time series using entropy is essential tool de-signing and controlling a nonlinear system. However, the existing methods have some dr…
An improved LogNNet classifier for IoT application
Hanif Heidari, Andrei Velichko
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 m…