Realization of Stochastic Neural Networks and Its Potential Applications

Autor:	Kari, S. Rahimi
Rok vydání:	2020
Předmět:	Computer Science - Neural and Evolutionary Computing Computer Science - Artificial Intelligence Computer Science - Networking and Internet Architecture Electrical Engineering and Systems Science - Signal Processing Statistics - Computation B.0 I.2.0
Druh dokumentu:	Working Paper
Popis:	Successive Cancellation Decoders have come a long way since the implementation of traditional SC decoders, but there still is a potential for improvement. The main struggle over the years was to find an optimal algorithm to implement them. Most of the proposed algorithms are not practical enough to be implemented in real-life. In this research, we aim to introduce the Efficiency of stochastic neural networks as an SC decoder and Find the possible ways of improving its performance and practicality. In this paper, after a brief introduction to stochastic neurons and SNNs, we introduce methods to realize Stochastic NNs on both deterministic and stochastic platforms. Comment: 6 pages, 11 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2011.06427 Zobrazit plný text záznamu View this record from Arxiv