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About Two Applications of Deep Learning in The Physical Layer of Communication Systems
1) Deep learning has proven useful for developing data-driven signal processing algorithms for challenging engineering problems by learning key features in input signals. 2) The paper discusses two applications of deep learning in the physical layer of communication systems, where deep learning can help solve practical problems that current solutions lack. 3) Artificial neural networks are introduced as function approximators that can learn input-output mappings from data. Neural networks can approximate continuous functions accurately using large but finite parameters.
Detailed Information
| Author: | ['prnjan'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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