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Artificial Intelligence for Molecular Communication
In this work, we give a general overview over the field molecular communication, discuss the challenges in the demodulations process of transmitted signals, and present approaches to these challenges that are based on artificial neural networks.
To Spike or Not to Spike? A Quantitative Comparison of SNN and CNN FPGA Implementations
Due to their compute- and data-intensive nature, CNN accelerators have been developed as ASICs or on FPGAs.
Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking Neural Networks
The motivation of using SNNs over conventional neural networks is rooted in the special computational aspects of SNNs, especially the very high degree of sparsity of neural output activations.
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