Event stream learning using spatio-temporal event surface

with multi-spike learning, we introduce a local search and gradient clipping mechanism to ensure the efficiency and stability of learning, which avoids other multi-spike learning rules’ time-consuming global search and the gradient explosion problem. Experimental results demonstrate the superior classification performance of our proposed model, especially for event streams with rich spatiotemporal dynamics.