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Using Affordable LED Arrays for Photo-Stimulation of Neurons
Published on: November 15, 2011
Reconfigurable nonlinear photonic activation function for photonic neural network based on non-volatile
Zefeng Xu1,2, Baoshan Tang3, Xiangyu Zhang3
1Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore, Singapore. xuzefeng@u.nus.edu.
Abstract:
Photonic neural network has been sought as an alternative solution to surpass the efficiency and speed bottlenecks of electronic neural network. Despite that the integrated Mach-Zehnder Interferometer (MZI) mesh can perform vector-matrix multiplication in photonic neural network, a programmable in-situ nonlinear activation function has not been proposed to date, suppressing further advancement of photonic neural network. Here, we demonstrate an efficient in-situ nonlinear accelerator comprising a unique solution-processed two-dimensional (2D) MoS2 Opto-Resistive RAM Switch (ORS), which exhibits tunable nonlinear resistance switching that allow us to introduce nonlinearity to the photonic neuron which overcomes the linear voltage-power relationship of typical photonic components. Our reconfigurable scheme enables implementation of a wide variety of nonlinear responses. Furthermore, we confirm its feasibility and capability for MNIST handwritten digit recognition, achieving a high accuracy of 91.6%. Our accelerator constitutes a major step towards the realization of in-situ photonic neural network and pave the way for the integration of photonic integrated circuits (PIC).

