Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems

Computer Science

• Hardware Implementation 100%
• Neural Network 100%
• Inference Process 66%
• Network Performance 33%
• Power Consumption 33%
• Trained Neural Network 33%
• Quantization 33%
• Information Representation 33%
• fault-tolerance 33%
• Classification Accuracy 33%
• Classification Task 33%
• Design Consideration 33%
• Training Process 33%
• Design Constraint 33%

Keyphrases

• Time-to-first-spike Coding 75%
• Processing Latency 50%
• Rate Coding 50%
• Burst Coding 50%
• Synaptic Noise 50%
• Noise Resilience 25%
• Noise Variation 25%
• Coding Time 25%
• Neural Coding Schemes 25%
• Implementation Networks 25%