Deep Learning in Spiking Phasor Neural Networks

Understand

Spiking Neural Networks (SNNs) have attracted the attention of the deep learning community for use in low-latency, low-power neuromorphic hardware, as well as models for understanding neuroscience.

• In this paper, we introduce Spiking Phasor Neural Networks (SPNNs).
• SPNNs are based on complex-valued Deep Neural Networks (DNNs), representing phases by spike times.
• Our model computes robustly employing a spike timing code and gradients can be formed using the complex domain.