Abstract —

I. INTRODUCTION  
A. Contributions of Our Survey  
B. Organization  

II. BACKGROUND  
A. Coding Formats of Spiking Signals  
B. Spiking Neuron Modelling and the Differences with Classic ANN Neuron  
C. SNN Model Training and Conversion Tools  

III. TECHNIQUES  
A. Topology Conversion  
B. Neuron Models on FPGA  
C. Optimization Techniques  
D. Technique Discussion  

IV. APPLICATIONS  
A. Image and Audio Processing  
B. Biomedical Applications  
C. Control Systems  
D. Autonomous Systems  
E. Robotics  
F. Event Vision Sensors  
G. Communication  

V. TREND  

VI. CONCLUSIONS