Figure 2 - available via license: Creative Commons Attribution 4.0 International
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(a) Base 4 − 3 − 2 network, light circles indicate activations, boxes indicate post-activations. (b) Example for Design A with 2 layers as input copies to each subsequent layer. The light circles indicate the linear operations/matrix-vector products. The results of the linear operation is averaged (single solid-blue circle) and fed through the activation function, producing the multiple version of the layers output (boxes). (c) Example of Design B.
Source publication
All analog signal processing is fundamentally subject to noise, and this is also the case in modern implementations of Optical Neural Networks (ONNs). Therefore, to mitigate noise in ONNs, we propose two designs that are constructed from a given, possibly trained, Neural Network (NN) that one wishes to implement. Both designs have the capability th...
Contexts in source publication
Context 1
... designs-illustrated in Figure 2-are built from a given NN for which an optical implementation is desired. Each design proposes a larger ONN by taking parts of the original NN, and duplicating and arranging them in a certain way. ...
Context 2
... that an example of Design A is presented in Fig- ure 2(b). Algorithm 1 constructs this tree-like network, given the desired number of copies n 0 , . . . ...
Context 3
... that an example of Design B is presented in Fig- ure 2(c). Algorithm 2 constructs this network, given a desired number of copies m in each layer. ...
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