Analog acceleration of deep learning using phase-change memory - ScienceDirect
Por um escritor misterioso
Descrição
Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses
Applied Sciences, Free Full-Text
Analog acceleration of deep learning using phase-change memory - ScienceDirect
Competing memristors for brain-inspired computing - ScienceDirect
PDF) In-Memory Computing for Machine Learning and Deep Learning
Emerging phase change memory devices using non-oxide semiconducting glasses - ScienceDirect
Analog acceleration of deep learning using phase-change memory - ScienceDirect
Electronics November-2 2023 - Browse Articles
Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials - Jeffrey S. Vetter, Prasanna Date, Farah Fahim, Shruti R. Kulkarni, Petro Maksymovych, A. Alec Talin, Marc Gonzalez
BNN An Ideal Architecture for Acceleration With Resistive in Memory Computation
Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials - Jeffrey S. Vetter, Prasanna Date, Farah Fahim, Shruti R. Kulkarni, Petro Maksymovych, A. Alec Talin, Marc Gonzalez
Analog acceleration of deep learning using phase-change memory - ScienceDirect
MXenes: promising 2D memristor materials for neuromorphic computing components: Trends in Chemistry
Reduction of the Weight-Decay Rate of Volatile Memory Synapses in an Analog Hardware Neural Network for Accurate and Scalable On-Chip Learning
Improvement of pattern recognition in spiking neural networks by modifying threshold parameter and using image inversion
de
por adulto (o preço varia de acordo com o tamanho do grupo)
