Synaptic plasticity is the biological process that produces synaptic weight changes through specific patterns of synaptic activity, a process that is thought to be the source of brain learning and memory. Therefore, simulating synaptic plasticity and learning functions and constructing artificial neural networks are the key to realizing neuromorphic brain computers in the future. Recently, the Sun Yang Research Group of the Institute of Physics of the Chinese Academy of Sciences has made new progress in the application of the Membrane, successfully applying the Membrane to the field of synaptic electronics.
Sun Yang's research group first proposed a non-volatile circuit component-memtranstor based on magnetoelectric coupling effect, and successfully demonstrated two-state storage and polymorphism at room temperature based on the mesander. Storage and Boolean logic operations. Recently, Sun Yang's research group Shang Dashan, associate researcher and Dr. Shen Jianyu, in the Ni/PMN-PT/Ni resynthesizer with room temperature and large magnetoelectric coupling effect, realized the electrical coupling value by adjusting the pulse trigger voltage and the number of pulses. The continuous reversible change mimics the increase in synaptic weights and the weakening behavior. They designed the typical synaptic plasticity behavior of pulse timing dependent plasticity (STDP) by designing a pulse voltage to trigger the waveform and superimposing the two sets of pulse waveforms. On this basis, they constructed a 4X4 neural network based on the Membrane, which simulates the static and dynamic learning functions of the picture by using the random noise learning method. This work is the first in the world to use the amplicator to simulate the synaptic plasticity and learning function, and proves the feasibility of constructing a low-power neural network based on the mesogen coupler, which provides the development of synaptic electronics and brain-like computing technology. A new way.
The work was supported by the Ministry of Science and Technology Key Research and Development Program, the National Natural Science Foundation and the Chinese Academy of Sciences project.
Article link: 
Https://doi.org/10.1002/adma.201706717
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