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In this chapter, we address some general theoretical issues concerning synaptic plasticity as the mechanism underlying learning in neural networks, in the context of neuromorphic VLSI systems, and provide a few implementation examples to illustrate the principles. It ties to Chapters 3 and 4 on neuromorphic sensors by proposing theoretical means for utilizing events for learning. It is an interesting...
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