Chapter

Neuro-inspired Computing Using Resistive Synaptic Devices

pp 73-95

Date:

TaOx-/TiO2-Based Synaptic Devices

  • I-Ting WangAffiliated withDepartment of Electronics Engineering and Institute of Electronics, National Chiao Tung University
  • , Tuo-Hung HouAffiliated withDepartment of Electronics Engineering and Institute of Electronics, National Chiao Tung University Email author 

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Abstract

The development of a high-density, low-power, and reliable synaptic device is essential in the implementation of highly anticipated hardware neural networks. Hence, numerous studies have investigated suitable two-terminal synaptic devices that precisely mimic biological synaptic features. In this chapter, we reviewed the development of a Ta/TaOx/TiO2/Ti resistive switching memory (RRAM) as a promising synaptic device technology for future neuromorphic computing systems. First, we reviewed the basic memory characteristics of the device and introduced a switching mechanism through electrical measurements and physical simulations. Second, we found that the device was particularly suitable for analog synapses, where several synaptic characteristics were demonstrated; moreover, we built a compact model to simulate these characteristics. Finally, a three-dimensional (3D) synaptic network was realized. In this chapter, we discussed the nonlinear weight update of the device and proposed an identical pulse training scheme for its improvement.