Simulation of all-optical demultiplexing utilizing two-photon absorption in semiconductor devices for high-speed OTDM networks

The performance of a two-photon absorption (TPA) based demultiplexer in an OTDM communication system is modeled. The demultiplexer is evaluated by comparing the electrical BER of the demultiplexed and detected channel to the optical BER of the signal before the demultiplexer. An error-free demultiplexing of a 250 Gbit/s signal (25 × 10 Gbit/s channels) is shown, using a 30:1 control-to-signal peak power ratio, with a TPA device with a bandwidth of 20 GHz should be possible. The device that is fabricated for TPA is a GaAs/AlAs PIN microcavity photodetector grown on a GaAs substrate

Generation of wavelength tunable optical pulses with SMSR exceeding 50 dB by self-seeding a gain-switched source containing two FP lasers

In this letter, we show the generation of shorter pulses (∼20 ps) that exhibit side mode suppression ratios (SMSR's) greater than 50 dB and wider tuning range (48.91 nm). Our technique is based on the self-seeding of a gain-switched source containing two FP lasers

Fault-tolerant networks-on-chip routing with coarse and fine-grained look-ahead

Fault tolerance and adaptive capabilities are challenges for modern networks-on-chip (NoC) due to the increase in physical defects in advanced manufacturing processes. Two novel adaptive routing algorithms, namely coarse and fine-grained (FG) look-ahead algorithms, are proposed in this paper to enhance 2-D mesh/torus NoC system fault-tolerant capabilities. These strategies use fault flag codes from neighboring nodes to obtain the status or conditions of real-time traffic in an NoC region, then calculate the path weights and choose the route to forward packets. This approach enables the router to minimize congestion for the adjacent connected channels and also to bypass a path with faulty channels by looking ahead at distant neighboring router paths. The novelty of the proposed routing algorithms is the weighted path selection strategies, which make near-optimal routing decisions to maintain the NoC system performance under high fault rates. Results show that the proposed routing algorithms can achieve performance improvement compared to other state of the art works under various traffic loads and high fault rates. The routing algorithm with FG look-ahead capability achieves a higher throughput compared with the coarse-grained approach under complex fault patterns. The hardware area/power overheads of both routing approaches are relatively low which does not prohibit scalability for large-scale NoC implementations

A Spiking Neural Network Model of the Medial Superior Olive Using Spike Timing Dependent Plasticity for Sound Localization

Sound localization can be defined as the ability to identify the position of an input sound source and is considered a powerful aspect of mammalian perception. For low frequency sounds, i.e., in the range 270 Hz–1.5 KHz, the mammalian auditory pathway achieves this by extracting the Interaural Time Difference between sound signals being received by the left and right ear. This processing is performed in a region of the brain known as the Medial Superior Olive (MSO). This paper presents a Spiking Neural Network (SNN) based model of the MSO. The network model is trained using the Spike Timing Dependent Plasticity learning rule using experimentally observed Head Related Transfer Function data in an adult domestic cat. The results presented demonstrate how the proposed SNN model is able to perform sound localization with an accuracy of 91.82% when an error tolerance of ±10° is used. For angular resolutions down to 2.5°, it will be demonstrated how software based simulations of the model incur significant computation times. The paper thus also addresses preliminary implementation on a Field Programmable Gate Array based hardware platform to accelerate system performance

Spiking neural network model of sound localisation using the interaural intensity difference

In this paper, a spiking neural network (SNN) architecture to simulate the sound localization ability of the mammalian auditory pathways using the interaural intensity difference cue is presented. The lateral superior olive was the inspiration for the architecture, which required the integration of an auditory periphery (cochlea) model and a model of the medial nucleus of the trapezoid body. The SNN uses leaky integrateand-fire excitatory and inhibitory spiking neurons, facilitating synapses and receptive fields. Experimentally derived headrelated transfer function (HRTF) acoustical data from adult domestic cats were employed to train and validate the localization ability of the architecture, training used the supervised learning algorithm called the remote supervision method to determine the azimuthal angles. The experimental results demonstrate that the architecture performs best when it is localizing high-frequency sound data in agreement with the biology, and also shows a high degree of robustness when the HRTF acoustical data is corrupted by noise

A comparison of sound localisation techniques using cross-correlation and spiking neural networks for mobile robotics

This paper outlines the development of a crosscorrelation algorithm and a spiking neural network (SNN) for sound localisation based on real sound recorded in a noisy and dynamic environment by a mobile robot. The SNN architecture aims to simulate the sound localisation ability of the mammalian auditory pathways by exploiting the binaural cue of interaural time difference (ITD). The medial superior olive was the inspiration for the SNN architecture which required the integration of an encoding layer which produced biologically realistic spike trains, a model of the bushy cells found in the cochlear nucleus and a supervised learning algorithm. The experimental results demonstrate that biologically inspired sound localisation achieved using a SNN can compare favourably to the more classical technique of cross-correlation

Speed of Rapid Serial Visual Presentation of Pictures, Numbers and Words Affects Event-Related Potential-Based Detection Accuracy

Rapid serial visual presentation (RSVP) based brain-computer interfaces (BCIs) can detect target images among a continuous stream of rapidly presented images, by classifying a viewer’s event related potentials (ERPs) associated with the target and non-targets images. Whilst the majority of RSVP-BCI studies to date have concentrated on the identification of a single type of image, namely pictures , here we study the capability of RSVP-BCI to detect three different target image types: pictures, numbers and words . The impact of presentation duration (speed) i.e., 100–200ms (5–10Hz), 200–300ms (3.3–5Hz) or 300–400ms (2.5–3.3Hz), is also investigated. 2-way repeated measure ANOVA on accuracies of detecting targets from non-target stimuli (ratio 1:9) measured via area under the receiver operator characteristics curve (AUC) for ${N}={15}$ subjects revealed a significant effect of factor Stimulus-Type ( pictures, numbers, words ) (F (2,28) = 7.243, ${p} = {0.003}$ ) and for Stimulus-Duration (F (2,28) = 5.591, p = 0.011). Furthermore, there is an interaction between stimulus type and duration: F (4,56) = 4.419, ${p} = {0.004}$ ). The results indicate that when designing RSVP-BCI paradigms, the content of the images and the rate at which images are presented impact on the accuracy of detection and hence these parameters are key experimental variables in protocol design and applications, which apply RSVP for multimodal image datasets

High-speed chromatic dispersion monitoring of a two-channel WDM system using a single TPA microcavity

Chromatic dispersion monitoring of two 160 Gb/s wavelength channels using a TPA Microcavity is presented. As the microcavity exhibits a wavelength resonance characteristic, a single device could monitor a number of different WDM-channels sequentially

Wavelength tuneable pulse monitoring using a Two-Photon-Absorption microcavity

Two Photon Absorption (TPA) is a non-linear optical-to-electrical conversion process that can be significantly enhanced by placing the active region within a resonance microcavity. The experiment confirmed the potential use of the microcavity structure for monitoring a single channel in multi-wavelength systems. The cavity can be designed for different applications depending on desired resonance width or cavity life time allowing the contrast ratio to be further improved. Due to the possibility of tuning the resonance wavelength by cavity tilting, a single device can be used to monitor a number of WDM channels without the need for additional optical filters

Dispersion insensitive, high-speed optical clock recovery based on a mode-locked laser diode

An investigation into the effects of varying levels of chromatic dispersion on a mode- locked laser diode optical clock recovery process is presented. Results demonstrate that this technique is invariant to input dispersion varying between +75 ps/nm