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张家斌、陈锡恒硕士论文答辩

与会者合影2

2022年5月23日,张家斌和陈锡恒两位同学成功举行了线上硕士论文答辩,论文题目分别是《基于COMSOL的时域与频域微磁学模拟研究》和《基于微磁学理论的磁结构调控与应用》。答辩委员会成员包括同济刘要稳教授、苏州纳米所曾中明研究院、天津大学兰金副教授、复旦大学吴义政教授。

两位同学经过共两个多小时的报告和质询答辩,答辩委员会一致建议授予张家斌和陈锡恒两位同学硕士学位。恭喜张家斌和陈锡恒!



A Hopfield neural network in magnetic films with natural learning

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In order to develop its ultimate potential, artificial intelligence must shift from the software-based towards hardware-based neuromorphic algorithms. For the artificial neural network, it requires materials and devices that are capable of emulating neuron-like activation and synapses with reprogrammable weights.

An adiabatic method to train Binary Neural Networks

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We proposed a new training method to realize binary neural networks. [1] This method can successfully train a conventional neural network into a binary one, where the neuron activations and/or weights take binary values of (+1 and -1). 

This work turned out to be compeletely in the field of Computer Science. …


© Jiang Xiao 2014