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1.
Opt Express ; 28(25): 37798-37810, 2020 Dec 07.
Artigo em Inglês | MEDLINE | ID: mdl-33379608

RESUMO

Swept-source optical coherence tomography (OCT) typically relies on expensive and complex swept-source lasers, the cost of which currently limits the suitability of OCT for new applications. In this work, we demonstrate spectrally sparse OCT utilizing randomly spaced low-bandwidth optical chirps, suitable for low-cost implementation with telecommunications grade devices. Micron scale distance estimation accuracy with a resolution of 40 µm at a standoff imaging distance greater than 10 cm is demonstrated using a stepped chirp approach with approximately 23% occupancy of 4 THz bandwidth. For imaging of sparse scenes, comparable performance to full bandwidth occupancy is verified for metallic targets.

2.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 422-425, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018018

RESUMO

Recent developments in wearable sensors demonstrate promising results for monitoring physiological status in effective and comfortable ways. One major challenge of physiological status assessment is the problem of transfer learning caused by the domain inconsistency of biosignals across users or different recording sessions from the same user. We propose an adversarial inference approach for transfer learning to extract disentangled nuisance-robust representations from physiological biosignal data in stress status level assessment. We exploit the trade-off between task-related features and person-discriminative information by using both an adversary network and a nuisance network to jointly manipulate and disentangle the learned latent representations by the encoder, which are then input to a discriminative classifier. Results on cross-subjects transfer evaluations demonstrate the benefits of the proposed adversarial framework, and thus show its capabilities to adapt to a broader range of subjects. Finally we highlight that our proposed adversarial transfer learning approach is also applicable to other deep feature learning frameworks.


Assuntos
Aprendizado Profundo , Aprendizagem , Aprendizado de Máquina , Informações Pessoalmente Identificáveis , Registros
3.
IEEE Signal Process Lett ; 26(5): 710-714, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-31814690

RESUMO

Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or recording session specific variability within EEG. Furthermore, recent methods have mostly trained and evaluated based on single session EEG data. We address this problem from an invariant representation learning perspective. We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations that can provide robustness in terms of longitudinal usability. Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected EEG data for person identification from half-second EEG epochs.

4.
Sci Rep ; 9(1): 1368, 2019 Feb 04.
Artigo em Inglês | MEDLINE | ID: mdl-30718661

RESUMO

Predicting physical response of an artificially structured material is of particular interest for scientific and engineering applications. Here we use deep learning to predict optical response of artificially engineered nanophotonic devices. In addition to predicting forward approximation of transmission response for any given topology, this approach allows us to inversely approximate designs for a targeted optical response. Our Deep Neural Network (DNN) could design compact (2.6 × 2.6 µm2) silicon-on-insulator (SOI)-based 1 × 2 power splitters with various target splitting ratios in a fraction of a second. This model is trained to minimize the reflection (to smaller than ~ -20 dB) while achieving maximum transmission efficiency above 90% and target splitting specifications. This approach paves the way for rapid design of integrated photonic components relying on complex nanostructures.

5.
Annu Int Conf IEEE Eng Med Biol Soc ; 2016: 854-858, 2016 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-28268458

RESUMO

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.


Assuntos
Identificação Biométrica/métodos , Eletroencefalografia/métodos , Potenciais Evocados/fisiologia , Algoritmos , Encéfalo/fisiologia , Eletroencefalografia/instrumentação , Desenho de Equipamento , Potencial Evocado P300/fisiologia , Humanos , Modelos Logísticos , Aprendizado de Máquina , Redes Neurais de Computação , Processamento de Sinais Assistido por Computador
6.
Opt Express ; 22(7): 8533-40, 2014 Apr 07.
Artigo em Inglês | MEDLINE | ID: mdl-24718225

RESUMO

A novel wavelength combiner using non-uniform refractive index distribution within a multimode interference device is proposed and simulated. The refractive index step creates separate localized modes with different effective refractive indices and two modes are strongly excited which form the basis of an interferometer. We applied the concept to 1.30/1.31 µm and 1.31/1.55 µm wavelength combiners on an InP substrate. The lengths of the devices are 1272 µm and 484 µm with simulated insertion losses of 0.6 dB and 0.67 dB respectively.

7.
Opt Express ; 22(7): 8798-812, 2014 Apr 07.
Artigo em Inglês | MEDLINE | ID: mdl-24718249

RESUMO

In this paper, we examine the performance of several modulation formats in more than four dimensions for coherent optical communications systems. We compare two high-dimensional modulation design methodologies based on spherical cutting of lattices and block coding of a 'base constellation' of binary phase shift keying (BPSK) on each dimension. The performances of modulation formats generated with these methodologies is analyzed in the asymptotic signal-to-noise ratio regime and for an additive white Gaussian noise (AWGN) channel. We then study the application of both types of high-dimensional modulation formats to standard single-mode fiber (SSMF) transmission systems. For modulation with spectral efficiencies comparable to dual-polarization (DP-) BPSK, polarization-switched quaternary phase shift keying (PS-QPSK) and DP-QPSK, we demonstrate SNR gains of up to 3 dB, 0.9 dB and 1 dB respectively, at a BER of 10(-3).

8.
Opt Express ; 20(26): B371-6, 2012 Dec 10.
Artigo em Inglês | MEDLINE | ID: mdl-23262875

RESUMO

A novel polarization splitter on an InP substrate utilizing an MMI coupler loaded with a dielectric and gold layer pad is proposed and simulated. A tilted joint is used for adjusting the phases of TE and TM modes. The MMI section is less than 540 µm. Simulations show that the device has a polarization extinction ratio over 23 dB and an insertion loss below 0.7 dB over the entire C-band for both TE and TM polarizations. The device design was optimized to maximize the wavelength range and tolerance for manufacturing variations.

9.
Opt Express ; 20(14): 15769-80, 2012 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-22772267

RESUMO

Fiber nonlinearity has become a major limiting factor to realize ultra-high-speed optical communications. We propose a fractionally-spaced equalizer which exploits a trained high-order statistics to deal with data-pattern dependent nonlinear impairments in fiber-optic communications. The computer simulation reveals that the proposed 3-tap equalizer improves Q-factor by more than 2 dB for long-haul transmissions of 5,230 km distance and 40 Gbps data rate. We also demonstrate that the joint use of a digital backpropagation (DBP) and the proposed equalizer offers an additional 1-2 dB performance improvement due to the channel shortening gain. A performance in high-speed transmissions of 100 Gbps and beyond is evaluated as well.

10.
Opt Express ; 20(9): 10163-9, 2012 Apr 23.
Artigo em Inglês | MEDLINE | ID: mdl-22535107

RESUMO

A mode-evolution-based polarization rotator-splitter built on InP substrate is proposed by combining a mode converter and an adiabatic asymmetric Y-coupler. The mode converter, consisting of a bi-level taper and a width taper, effectively converts the fundamental TM mode into the second order TE mode without changing the polarization of the fundamental TE mode. The following adiabatic asymmetric Y-coupler splits the fundamental and the second order TE modes and also converts the second order TE mode into the fundamental TE mode. A shallow etched structure is proposed for the width taper to enhance the polarization conversion efficiency. The device has a total length of 1350 µm, a polarization extinction ratio over 25 dB and an insertion loss below 0.5 dB both for TE and TM modes, over the wavelength range from 1528 to 1612 nm covering all C + L band. Because the device is designed based on mode evolution principle, it has a large fabrication tolerance. The insertion loss remains below 1 dB and the polarization extinction ratio remains over 17 dB with respect to a width variation of +/- 0.12 µm at the wavelength of 1570 nm, or +/- 0.08 µm over the entire C + L band.


Assuntos
Índio/química , Fosfinas/química , Refratometria/instrumentação , Ressonância de Plasmônio de Superfície/instrumentação , Desenho de Equipamento , Análise de Falha de Equipamento
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