11. Introduction to neuromorphic programming

Chapter 11

This chapter will take the first few steps toward neuromorphic programming. We will start with emerging theoretical concepts on neuromorphic computing (e.g., complexity theory) and move on to neural codes. Key neuromorphic programming paradigms will be discussed, ranging from low-level PyNN programming which was utilized for the SpiNNaker to Corelet, developed by IBM Research to support high-level neuromorphic programming for the TrueNorth chip. Finally, we will dis- cuss key algorithms for training SNNs toward supervised neuromorphic machine learning.