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Brain-like computing has the advantages of self-learning, parallel computing, and low energy consumption, and is considered to be an important technology to overcome computer bottlenecks. With the advancement of electronic technology, various types of bionic synapses have been widely studied, however, the human brain has more than 10^11 neuron cells and over 10^16 synapses, and it is quite difficult to complete this architecture using traditional silicon manufacturing processes. Therefore, it is very important to develop new types of synaptic components.

This project "Design, Manufacture and Application Research of Bionic Synapse with Visual Cognitive Function" is a continuation project, using oxide/organic semiconductor (Organic/Oxide) to make light-sensitive multi-terminal bionic synapses, aiming to solve the previous problems.

The topics are focused on (1) Carrying out the large-area manufacturing technology of the array-type dielectric layer with polarization effect for synaptic transistors, (2)The design and reproduction of the light-sensitive multi-terminal input bionic synapse, including plasticity weight control and hysteresis engineering, and (3)The manufacturing process/simulation/application of the visual assistant pattern recognition of artificial neural network.

The advantage of this project is that it uses a complementary architecture, a wide range of operable signals, and the overall process is facile and low cost. The formed synapses have the advantages of flexibility, mechanical robustness, and strong plasticity and learning effects. Project goal: Complete the basic unit with synaptic function, and conduct lightstimuli verification of pair pulse facilitation (PPF), plasticity synaptic current model (PSC), spike timing dependent plasticity (STDP), especially long-term potentiation (LTP), and long-term depression (LTD). Establish a light-stimuli neuro synaptic circuit model, SPICE or numerical model, and use it to evaluate a 28x28 artificial neural network, conduct MINST pattern recognition verification, test its learning and memory function and accuracy, and can also be used as a biological synapse demonstration teaching aid.

  • Field: Engineering
  • School: National Changhua University of Education
  • Organizer: Graduate Institute of Photonics
  • Period of Apply: ~2023/12
  • Term: ~2023/6
  • Fee: None
  • Contact Person:Prof. Yu-Wu Wang
  • Email:wangyw@cc.ncue.edu.tw
  • Phone:+886-4-7232105#3380

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