Orthogonal multipulse modulation for next-generation datacommunication links

Orthogonal multipulse modulation is demonstrated to allow ≈30 Gb/s real-time transmission over multimode fibre using an 850 nm VCSEL. The scheme eases considerably component bandwidth requirements compared with conventional NRZ modulation. © 2011 OSA.

Adaptive lenses based on polarization modulation

We present and demonstrate a technique for producing a high-speed variable focus lens using a fixed birefringent lens and a ferroelectric liquid crystal cell as a polarization switch. A calcite lenses with ordinary and extraordinary focal lengths of 109mm and 88mm respectively, was used to demonstrate focus switching at frequencies of up to 3kHz. Two identical lenses and a single liquid crystal were also used to demonstrate zoom.

Phase modulation with polymer-dispersed liquid crystals

We report on work on producing phase-only polymer-dispersed liquid crystals for use in spatial light modulators for adaptive optics. The aim is to assess the magnitude of the achievable phase shifts and the associated slew rate. We describe our methodology of producing devices and present our initial results.

Progress in ultra-high modulation efficiency tapered lasers for free-space communications

Simultaneous high power (2W), high modulation speed (1Gb/s) and high modulation efficiency (14 W/A) operation of a two-electrode tapered laser is reported. © 2011 IEEE.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions

Indirect modulation of a terahertz quantum cascade laser using gate tunable graphene

We bring together two areas of terahertz (THz) technology that have benefited from recent advancements in research, i.e., graphene, a material that has plasmonic resonances in the THz frequency, and quantum cascade lasers (QCLs), a compact electrically driven unipolar source of THz radiation. We demonstrate the use of single-layer large-area graphene to indirectly modulate a THz QCL operating at 2.0 THz. By tuning the Fermi level of the graphene via a capacitively coupled backgate voltage, the optical conductivity and, hence, the THz transmission can be varied. We show that, by changing the pulsing frequency of the backgate, the THz transmission can be altered. We also show that, by varying the pulsing frequency of the backgate from tens of Hz to a few kHz, the amplitude-modulated THz signal can be switched by 15% from a low state to a high state. © 2009-2012 IEEE.

Mismatched shaping schemes for bit-interleaved coded modulation

We consider bit-interleaved coded modulation (BICM) schemes where, instead of the true bit or symbol probabilities and the constellation used at the transmitter, the decoder uses arbitrary probabilities or reference constellations. We study the corresponding low- and high- signal-to-noise-ratio regimes and show that even in the presence of this extra sources of mismatch, BICM has a negligible penalty with respect to coded modulation. © 2012 IEEE.

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.

28 Gb/s unequalized PAM3 modulation of an 850 nm VCSEL for next-generation datacommunication links

An 850 nm vertical-cavity surface-emitting laser is modulated at 28 Gb/s using pulseamplitude modulation with three levels. Unequalized transmission over 100 m of OM3 MMF is demonstrated, with advantages over NRZ and PAM4 modulation. © 2012 OSA.

Modulation of somatosensory processing by action.

Psychophysical evidence suggests that sensations arising from our own movements are diminished when predicted by motor forward models and that these models may also encode the timing and intensity of movement. Here we report a functional magnetic resonance imaging study in which the effects on sensation of varying the occurrence, timing and force of movements were measured. We observed that tactile-related activity in a region of secondary somatosensory cortex is reduced when sensation is associated with movement and further that this reduction is maximal when movement and sensation occur synchronously. Motor force is not represented in the degree of attenuation but rather in the magnitude of this region's response. These findings provide neurophysiological correlates of previously-observed behavioural forward-model phenomena, and advocate the adopted approach for the study of clinical conditions in which forward-model deficits have been posited to play a crucial role.

Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.