分析 Spiking Neural Networks (SNN) 和脑启发计算论文,提炼可复用的技术模式和实现指南。Use when analyzing papers about: spiking neural networks, brain-inspired computing, neuromorphic systems, biological learning rules, SNN architectures, or extracting implementation patterns from neuroscience papers.
Scanned 9/11/2026
Install to Claude Code
npx -y skills add hiyenwong/ai_collection --skill brain-inspired-snn-pattern-analysis --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Brain Inspired Snn Pattern Analysis?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/hiyenwong-brain-inspired-snn-pattern-analysis-84706841)More formats (shields.io, HTML) on the badges page.
---
name: brain-inspired-snn-pattern-analysis
description: "分析 Spiking Neural Networks (SNN) 和脑启发计算论文,提炼可复用的技术模式和实现指南。Use when analyzing papers about: spiking neural networks, brain-inspired computing, neuromorphic systems, biological learning rules, SNN architectures, or extracting implementation patterns from neuroscience papers."
---
# Brain-Inspired SNN Pattern Analysis
分析脑启发计算和 SNN 论文,提炼技术模式。
## Activation Keywords
- SNN pattern analysis
- spiking neural network pattern
- brain-inspired computing analysis
- 脑启发计算模式
- 神经形态计算分析
- extract SNN implementation pattern
## Workflow
### Step 1: Paper Analysis
识别论文的核心技术:
- 网络架构(VLIF, LIF, Izhikevich 等)
- 学习规则(STDP, Forward-Forward, Backprop-free)
- 应用领域(视觉、医疗、时序处理)
- 关键创新点
### Step 2: Pattern Extraction
提取可复用模式:
```
Pattern: [模式名称]
Category: [架构|学习规则|优化|应用]
Key Concepts: [关键词]
Implementation Hint: [实现提示]
```
### Step 3: Code Template Generation
基于模式生成代码框架(Python/PyTorch)
## Common Patterns (from kg.db analysis)
| Pattern | Papers | Key Concepts |
|---------|--------|--------------|
| Energy-Efficient SNN | Predictive Insulin Delivery | energy-efficient, medical AI, SNN |
| VLIF Neuron | Image Deraining | VLIF neuron, low-level vision |
| Brain Connectivity Viz | BrainRing | chord diagrams, functional connectivity |
| Neural Cellular Automata | BraiNCA | attention, long-range connections |
| EEG Foundation Model | DeeperBrain | neuro-grounded, neural dynamics |
| Forward-Forward Learning | Backprop-free SNN | biological learning, training |
| Quantized SNN | Integer-State Dynamics | hardware acceleration, finite precision |
| Spiking State-Space | Parallelized Connectome | spatiotemporal recurrence, parallel scan |
## Output Format
```markdown
## 🧠 SNN Pattern Analysis
### Paper: [Title]
### Core Innovation: [描述]
### Pattern Template
```python
# Pattern: [名称]
class [PatternName]:
def __init__(self):
# Key components from paper
pass
```
### Implementation Notes
- [关键实现要点]
- [注意事项]
```
## Resources
- kg.db: 知识图谱数据库
- kg_tool: `/Users/hiyenwong/.openclaw/workspace/scripts/kg_tool/target/release/kg_tool`Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!