Artificial Shape Perception Retina Network Based on Tunable Memristive Neurons
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Updated: Feb 5, 2026

Author Spotlight: Using the Split Retina Technique for Enhanced Access and Accelerated Experiments
Published on: January 16, 2024
Lin Bao1, Jian Kang1, Yichen Fang1
1Institute of Microelectronics, Peking University, Beijing, 100871, China.
Abstract:
Retina shows an extremely high signal processing efficiency because of its specific signal processing strategy which called computing in sensor. In retina, photoreceptor cells encode light signals into spikes and ganglion cells finish the shape perception process. In order to realize the neuromorphic vision sensor, the one-transistor-one-memristor (1T1M) structure which formed by one memristor and one MOSFET in serial is used to construct photoreceptor cell and ganglion cell. The voltage changes between two terminals of memristor and MOSFET can mimic the changes of membrane potential caused by spikes and illumination respectively. In this paper, the tunable memristive neurons with 1T1M structures are built. According to the concept of receptive field of ganglion cells (GCs) in the retina, the artificial shape perception retina network is constructed with these memristive neurons. The final results show that the artificial retina can extract shape information from the image and transfer it into spike frequency realizing the function of computing in sensor.
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