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Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network

机译：人工智能脑激发硬件：物理模型尖峰神经网络加速学习

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Timo Wunderlich; Akos F. Kungl; Eric Müller; Johannes Schemmel; Mihai Petrovici;
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年度 2019
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1. Advances in artificial neural networks, machine learning and computational intelligence Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018) [J] . Oneto Luca, Bunte Kerstin, Schleif Frank-Michael Neurocomputing . 2019,第MAYa21期

机译：人工神经网络，机器学习和计算智能的进步选自第26届欧洲人工神经网络，计算智能和机器学习研讨会（ESANN 2018）的论文
2. Advances in artificial neural networks, machine learning and computational intelligence Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018) [J] . Oneto Luca, Bunte Kerstin, Schleif Frank-Michael Neurocomputing . 2019,第May21期

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3. A CMOS Spiking Neuron for Brain-Inspired Neural Networks With Resistive Synapses and In Situ Learning [J] . Wu Xinyu, Saxena Vishal, Zhu Kehan, Circuits and Systems II: Express Briefs, IEEE Transactions on . 2015,第11期

机译：带有脑突触和原位学习功能的脑神经网络的CMOS尖峰神经元。
4. Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network [C] . Timo Wunderlich, Akos F. Kungl, Eric Mueller, International Conference on Artificial Neural Networks . 2019

机译：受大脑启发的人工智能硬件：物理模型尖刺神经网络中的加速学习
5. The Art of Artificial Neural Networks: Emergent Creativity in Artificial Intelligence [D] . Rajkumar, Vijay Gautham 2018

机译：人工神经网络的艺术：人工智能中的新兴创造力
6. Comparison of Artificial and Spiking Neural Networks on Digital Hardware [O] . Simon Davidson, Steve B. Furber 2021

机译：数字硬件上人工和尖峰神经网络的比较
7. A CMOS Spiking Neuron for Brain-Inspired Neural Networks with Resistive Synapses and \u3cem\u3eIn-Situ\u3c/em\u3e Learning [O] . Wu, Xinyu, Saxena, Vishal, Zhu, Kehan, 2015

机译：用于具有电阻突触和\ u3cem \ u3eIn-Situ \ u3c / em \ u3e学习的大脑启发式神经网络的CMOS尖峰神经元

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network

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