🔬

spiking-neural-network

Build brain-like neural networks that communicate through discrete spikes like biological neurons. Explore SNNs - the third generation of neural networks that could be 1000x more energy efficient than deep learning.

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這是什麼?

🎯 模擬器提示

📚 術語表

SNN
尖峰神經網路
Spike
短暫的電脈衝(動作電位)
LIF
洩漏積分和激發神經元模型
STDP
尖峰時間相關的可塑性
MembranePotential
神經元電壓
Threshold
神經元放電的電壓
RefractoryPeriod
神經元無法放電時尖峰後的時間
RateCoding
以尖峰頻率編碼的訊息
TemporalCoding
以尖峰時序編碼的訊息
Neuromorphic
類腦計算

🏆 關鍵人物

Wolfgang Maass

液態狀態機、SNN 理論

Carver Mead

創造“神經形態”,先驅

Henry Markram

藍腦計劃,STDP 發現

Steve Furber

SpiNNaker開發

Mike Davies

英特爾Loihi架構師

🎓 學習資源

💬 給學習者的話

{'encouragement': "You're learning about the third generation of neural networks - one that could be 1000x more efficient than current AI. SNNs represent the bridge between neuroscience and artificial intelligence.", 'reminder': 'The brain is still the most efficient intelligent system we know. SNNs try to learn from its principles - sparse, event-driven, temporal computation.', 'action': 'Build spiking neurons in the simulator. Watch STDP learning unfold. See how timing affects connections. Experience computation through spikes.', 'dream': 'A neuroscientist from Kenya might unlock new SNN learning rules. An engineer from Nigeria might design breakthrough neuromorphic chips. Brain-inspired AI needs global perspectives.', 'wiaVision': "WIA Pin Code believes brain-inspired computing should be understood globally. If we can match the brain's efficiency, AI becomes accessible to everyone, everywhere."}

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