Litcius/Paper detail

Reduction 93.7% time and power consumption using a memristor-based imprecise gradient update algorithm

Jie Li, Guangdong Zhou, Yingying Li, Jiahao Chen, Yuan Ge, Yan Mo, Yuanlei Yang, Xicong Qian, Wenwu Jiang, Hongbo Liu, Mingjian Guo, Lidan Wang, Shukai Duan

2021Artificial Intelligence Review20 citationsDOI

Topics & Concepts

MemristorNeuromorphic engineeringComputer scienceMNIST databasePerceptronReduction (mathematics)MemistorArtificial neural networkMultilayer perceptronBlock (permutation group theory)Dropout (neural networks)Artificial intelligenceAlgorithmComputer engineeringElectronic engineeringMachine learningResistive random-access memoryVoltageElectrical engineeringMathematicsGeometryEngineeringAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesCCD and CMOS Imaging Sensors
Reduction 93.7% time and power consumption using a memristor-based imprecise gradient update algorithm | Litcius