Practice Spiking Neural Networks (snns) (6.2.1) - Neuromorphic Computing and Hardware Accelerators

Practice: Spiking Neural Networks (SNNs)

Lesson 6.2.1Neuromorphic Computing and Hardware Accelerators

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10 questions

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6 sample questions

Question 1.
What is a Spiking Neural Network?
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Think about how neurons in the brain communicate.
Question 2.
What is meant by the term 'threshold' in SNNs?
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Consider what triggers a neuron to send a spike.
3Question 3.
What is the main method of communication in Spiking Neural Networks?
- Continuous values
- Discreet spikes
- Analog signals
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Think about how biological neurons signal each other.
4Question 4.
True or False: SNNs are less efficient than traditional neural networks.
- True
- False
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Consider the method of spike-based communication.
Question 5.
Design a simple spiking model for a robotic hand that reacts to touch. Discuss how you would implement spikes and thresholds.
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Think about how you would want the hand to react to different pressures.
Question 6.
Summarize the potential limitations of SNNs in comparison to traditional neural networks in non-time-critical applications.
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Consider the trade-offs of speed versus efficiency.

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