Search Results for author: Thomas Ferreira de Lima

Found 8 papers, 2 papers with code

Fast WDM provisioning with minimal probing: the first field experiments for DC exchanges

no code implementations14 Sep 2023 Hideki Nishizawa, Toru Mano, Thomas Ferreira de Lima, Yue-Kai Huang, Zehao Wang, Wataru Ishida, Masahisa Kawashima, Ezra Ip, Andrea D'Amico, Seiji Okamoto, Takeru Inoue, Kazuya Anazawa, Vittorio Curri, Gil Zussman, Daniel Kilper, Tingjun Chen, Ting Wang, Koji Asahi, Koichi Takasugi

Then, using field fibers deployed in the NSF COSMOS testbed (deployed in an urban area), a Linux-based transmission device software architecture, and coherent transceivers with different optical frequency ranges, modulators, and modulation formats, the fast WDM provisioning of an optical path was completed within 6 minutes (with a Q-factor error of about 0. 7 dB).

Real-Time Blind Photonic Interference Cancellation for mmWave MIMO

no code implementations6 May 2023 Joshua C. Lederman, Weipeng Zhang, Thomas Ferreira de Lima, Eric C. Blow, Simon Bilodeau, Bhavin J. Shastri, Paul R. Prucnal

Multiple-input multiple-output (MIMO) mmWave devices broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates.

Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation

no code implementations7 May 2022 Weipeng Zhang, Alexander Tait, Chaoran Huang, Thomas Ferreira de Lima, Simon Bilodeau, Eric Blow, Aashu Jha, Bhavin J. Shastri, Paul Prucnal

The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues.

blind source separation

A Photonic-Circuits-Inspired Compact Network: Toward Real-Time Wireless Signal Classification at the Edge

1 code implementation25 Jun 2021 Hsuan-Tung Peng, Joshua Lederman, Lei Xu, Thomas Ferreira de Lima, Chaoran Huang, Bhavin Shastri, David Rosenbluth, Paul Prucnal

In addition, compact and integratable hardware platforms which can implement ML models at the chip scale will find much broader application to wireless communication networks.

Classification

Photonics for artificial intelligence and neuromorphic computing

no code implementations30 Oct 2020 Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright, Paul R. Prucnal

Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms.

Medical Diagnosis

Noise Analysis of Photonic Modulator Neurons

no code implementations17 Jul 2019 Thomas Ferreira de Lima, Alexander N. Tait, Hooman Saeidi, Mitchell A. Nahmias, Hsuan-Tung Peng, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal

Here, we examine modulator-based photonic neuron circuits with passive and active transimpedance gains, with special attention to the sources of noise propagation.

Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)

1 code implementation23 Apr 2019 Viraj Bangari, Bicky A. Marquez, Heidi B. Miller, Alexander N. Tait, Mitchell A. Nahmias, Thomas Ferreira de Lima, Hsuan-Tung Peng, Paul R. Prucnal, Bhavin J. Shastri

Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for extracting features from large datasets for applications such as computer vision and natural language processing.

Neuromorphic Silicon Photonic Networks

no code implementations5 Nov 2016 Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou, Allie X. Wu, Mitchell A. Nahmias, Bhavin J. Shastri, Paul R. Prucnal

At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

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