Details

Autor(en) / Beteiligte

• Tolias, Leonidas K.
• Shastri, Bhavin J.
• Nahmias, Mitchell M.
• Tait, Alexander N.
• de Lima, Thomas Ferrieira
• Prucnal, Paul R.

Titel

Spike train encoding of analog signals in a graphene fiber ring laser

Ist Teil von

• 2015 IEEE MIT Undergraduate Research Technology Conference (URTC), 2015, p.1-3

Ort / Verlag

IEEE

Erscheinungsjahr

2015

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Spiking neural networks (SNN) have inherent advantages over traditional computing architectures for many computational problems such as adaptive control, sensory processing, and pattern recognition. Recently, a graphene-based fiber laser has been shown that demonstrates all the key properties of spike processing: logic-level restoration, cascadability and input-output isolation, in one device[1]. Here, we show that this device is able to perform unique nonlinear operations on analog input signals, including the ability to convert those signals into spike train outputs. This represents a stepping stone towards practical implementations of laser devices that can perform spike-based operations on high frequency analog signals.