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All optical neural network

An optical and neuron technology, applied in the field of deep learning artificial neural network

Pending Publication Date: 2020-10-27
THE HONG KONG UNIV OF SCI & TECH
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Problems solved by technology

However, nonlinear transfer functions are usually implemented electronically, as implementing nonlinear transfer functions optically has proven challenging

Method used

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  • All optical neural network
  • All optical neural network
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Embodiment Construction

[0045] Layers of artificial neurons can be simulated in the optical path using optical components to perform linear and nonlinear transformations within the optical medium. Linear summation can be achieved by modulating optical amplitude or phase at various positions in the signal (e.g., multiplying components of the input signal by weights) and then combining the modulated optical signals to achieve a linear summation (e.g., combining the weighted components to produce a weighted sum) . The different optical neurons of the layer can be implemented using different diffraction gratings to separate the components of the input signal according to the various optical neurons in the layer. Optical nonlinear transformations can be performed by tuning nonlinear optical media to have electromagnetically induced transparency (EIT) properties that, when illuminated by the output of a linear transformation, function similarly to conventional activation functions. In other words, the cou...

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Abstract

An all-optical neural network that utilizes light beams and optical components to implement layers of the neural network is disclosed herein. The all-optical neural network includes an input layer, zero or more hidden layers, and an output layer. Each layer of the neural network is configured to simulate linear and nonlinear operations of a conventional artificial neural network neuron on an optical signal. In an embodiment, the optical linear operation is performed by a spatial light modulator and an optical lens. The optical lens performs a Fourier transformation on the set of light beams and sums light beams with similar propagation orientations. The optical nonlinear operation is implemented utilizing a nonlinear optical medium having an electromagnetically induced transparency characteristic whose transmission of a probe beam of light is controlled by the intermediate output of a coupling beam of light from the optical linear operation.

Description

[0001] priority claim [0002] This application claims the benefit of U.S. Provisional Application No. 62 / 834,005, entitled "All-Optical Neural Networks," filed April 15, 2019, the entire contents of which are incorporated herein by reference. technical field [0003] The present disclosure relates to deep learning artificial neural networks. More specifically, the present disclosure is directed to artificial neural networks implemented with optical components to perform calculations using light as a medium. Background technique [0004] Machine learning based on Artificial Neural Networks (ANNs) has grown significantly over the past few decades. Machine learning provides general techniques for systems to learn from data and make decisions with minimal human intervention. As a machine learning algorithm, ANN is a computational model based on the neural structure of the brain, in which a collection of connected nodes called artificial neurons is implemented. With the exten...

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Application Information

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IPC IPC(8): G06N3/067G06N3/08
CPCG06N3/067G06N3/084G02F1/3515G06N3/04G06N3/0675G02B27/12G02F2203/01G06N3/08
Inventor 杜胜望刘军伟左瀛李博瀚赵宇君蒋悦陈鹏陈宥全
Owner THE HONG KONG UNIV OF SCI & TECH
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