ABSTRACT
Algorithms power the digital world. As machine learning algorithms aim to transform numerous fields of research and practice, the cross-section between brain sciences and algorithm design is growing in importance. This cross-section has been proven to provide extraordinary cross-pollination to both ends, including the developments of Deep Neural Networkss (DNNs), Convolutional Neural Networkss (CNNs), and Recurrent Neural Networkss (RNNs). This chapter will introduce the perspective of the algorithm designer on neuromorphic engineering which aims to develop applications ranging from adaptive robotic control to object recognition with increased accuracy and precision. In this chapter we will discuss, neuromorphic software development environments and the rationale of using Spiking Neural Networkss (SNNs) for algorithm design.
