KEYWORDS: Neurons, Tunable filters, Electronic filtering, Signal filtering, Data modeling, Machine learning, Linear filtering, Artificial intelligence, Nonlinear filtering, Education and training
In this paper, starting from heart cardiovascular data of human beings, we provide a neuron network based mathematical computation method to capture the nonlinear dynamics of cardiovascular data and proposed an AI based approach to predict cardiovascular data and then classify between a healthy data model and an ill data model. From the cardiovascular nonlinear dynamics model, we further elucidate its similarity to Wiener problem as a special case and Kalman filtering. This clarify interpret able of AI and neuron network based approach for heartbeat data science.
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