A Survey of Stochastic Computing Neural Networks for Machine Learning Applications

• Published in: IEEE transaction on neural networks and learning systems Vol. 32; no. 7; pp. 2809 - 2824
• Main Authors: Liu, Yidong, Liu, Siting, Wang, Yanzhi, Lombardi, Fabrizio, Han, Jie
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Belief networks; Biological neural networks; Computation; Energy consumption; Hardware; Humans; Inference; Learning algorithms; Machine Learning; Multilayer perceptrons; Neural network (NN); Neural networks; Neural Networks, Computer; Neurons; Polls & surveys; Power consumption; stochastic computing (SC); Stochastic Processes; Stochasticity; Training

Neural networks (NNs) are effective machine learning models that require significant hardware and energy consumption in their computing process. To implement NNs, stochastic computing (SC) has been proposed to achieve a tradeoff between hardware efficiency and computing performance. In an SC NN, har...