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By performing most of the operations on the TD received symbols and sharing operations, the overall computational load required to implement both algorithms is affordable for real-time implementations.
The real-time implementations are also discussed in the presentation slides.
The toolset enables specification and analysis of real-time implementations of control applications.
Hardware real-time implementations of Spiking Neuron Networks (SNN) are wanted for multiple applications.
Furthermore, we investigate if incremental algorithms and real-time implementations can be achieved for background/foreground separation.
In terms of computational complexity, our method runs in linear time, making it feasible for real-time implementations.
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Real-time implementation results are presented.
This allows for real-time implementation.
These facilitate the real-time implementation of the control system.
Therefore, a real-time implementation for industrial processes is feasible.
This final controller is finally assessed with real-time implementation.
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