Showing papers by "Thomas Ferreira de Lima published in 2015"
TL;DR: This work presents a physically realistic optoelectronic simulation model of a circuit for dynamical laser neural networks and describes the physics, dynamics, and parasitics of one network node, which includes a bank of filters, a photodetector, and excitable laser.
Abstract: The combination of ultrafast laser dynamics and dense on-chip multiwavelength networking could potentially address new domains of real-time signal processing that require both speed and complexity. We present a physically realistic optoelectronic simulation model of a circuit for dynamical laser neural networks and verify its behavior. We describe the physics, dynamics, and parasitics of one network node, which includes a bank of filters, a photodetector, and excitable laser. This unconventional circuit exhibits both cascadability and fan-in, critical properties for the large-scale networking of information processors based on laser excitability. In addition, it can be instantiated on a photonic integrated circuit platform and requires no off-chip optical I/O. Our proposed processing system could find use in emerging applications, including cognitive radio and low-latency control.
36 citations
13 Jul 2015
TL;DR: In this article, an integrated optoelectronic circuit capable of tracking on real-time the first principal component of an array of wideband analog RF signals is proposed. But the circuit is not suitable for wideband PCA.
Abstract: We propose an integrated optoelectronic circuit capable of tracking on real-time the first principal component of an array of wideband analog RF signals. Preliminary results warrants the suitability of photonic components for wideband PCA.
1 citations
01 Jan 2015
TL;DR: A microwave photonic system that iteratively performs principal component analysis on partially correlated, 8-channel, 13 Gbaud signals is presented, able to adapt to oscillations in interchannel correlations and follow changing principal components.
Abstract: We propose and experimentally demonstrate a microwave photonic system that iteratively performs principal component analysis on partially correlated, 8-channel, 13 Gbaud signals. The system that is presented is able to adapt to oscillations in interchannel correlations and follow changing principal components. The system provides advantages in bandwidth performance and fan-in scalability that are far superior to electronic counterparts. Wideband, multidimensional techniques are relevant to >10 GHz cognitive radio systems and could bring solutions for intelligent radio communications and information sensing, including spectral sensing.