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.

Towards a fast electro-thermo-mechanical IGBT/Diode simulation framework for design of reliable power electronic converters

This paper describes a methodology that enables fast and reasonably accurate prediction of the reliability of power electronic modules featuring IGBTs and p-i-n diodes, by taking into account thermo-mechanical failure mechanisms of the devices and their associated packaging. In brief, the proposed simulation framework performs two main tasks which are tightly linked together: (i) the generation of the power devices' transient thermal response for realistic long load cycles and (ii) the prediction of the power modules' lifetime based on the obtained temperature profiles. In doing so the first task employs compact, physics-based device models, power losses lookup tables and polynomials and combined material-failure and thermal modelling, while the second task uses advanced reliability tests for failure mode and time-to-failure estimation. The proposed technique is intended to be utilised as a design/optimisation tool for reliable power electronic converters, since it allows easy and fast investigation of the effects that changes in circuit topology or devices' characteristics and packaging have on the reliability of the employed power electronic modules. © 2012 IEEE.

Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray.

Predictions about sensory input exert a dominant effect on what we perceive, and this is particularly true for the experience of pain. However, it remains unclear what component of prediction, from an information-theoretic perspective, controls this effect. We used a vicarious pain observation paradigm to study how the underlying statistics of predictive information modulate experience. Subjects observed judgments that a group of people made to a painful thermal stimulus, before receiving the same stimulus themselves. We show that the mean observed rating exerted a strong assimilative effect on subjective pain. In addition, we show that observed uncertainty had a specific and potent hyperalgesic effect. Using computational functional magnetic resonance imaging, we found that this effect correlated with activity in the periaqueductal gray. Our results provide evidence for a novel form of cognitive hyperalgesia relating to perceptual uncertainty, induced here by vicarious observation, with control mediated by the brainstem pain modulatory system.

Modulation of pain ratings by expectation and uncertainty: Behavioral characteristics and anticipatory neural correlates.

Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

Modulation of pain processing in hyperalgesia by cognitive demand.

The relationship between pain and cognitive function is of theoretical and clinical interest, exemplified by observations that attention-demanding activities reduce pain in chronically afflicted patients. Previous studies have concentrated on phasic pain, which bears little correspondence to clinical pain conditions. Indeed, phasic pain is often associated with differential or opposing effects to tonic pain in behavioral, lesion, and pharmacological studies. To address how cognitive engagement interacts with tonic pain, we assessed the influence of an attention-demanding cognitive task on pain-evoked neural responses in an experimental model of chronic pain, the capsaicin-induced heat hyperalgesia model. Using functional magnetic resonance imaging (fMRI), we show that activity in the orbitofrontal and medial prefrontal cortices, insula, and cerebellum correlates with the intensity of tonic pain. This pain-related activity in medial prefrontal cortex and cerebellum was modulated by the demand level of the cognitive task. Our findings highlight a role for these structures in the integration of motivational and cognitive functions associated with a physiological state of injury. Within the limitations of an experimental model of pain, we suggest that the findings are relevant to understanding both the neurobiology and pathophysiology of chronic pain and its amelioration by cognitive strategies.

Feasibility of 100G ethernet enabled by carrierless amplitude/phase modulation and optical OFDM

For the first time, simulations have analysed the feasibility of 100Gb/s CAP and OFDM systems over SMF links using 18.6GHz directly modulated lasers. We have shown that CAP-16/16- QAM-OFDM and CAP-64/64-QAM-OFDM over a single channel can successfully support transmission over 2km SMF, with power dissipation of ∼2 times that of a 4×25Gb/s NRZ system. © 2012 OSA.

FEC-free 50 m 1.5 Gb/s plastic optical fibre link using CAP modulation for home networks

LED-based carrierless amplitude and phase modulation is investigated for a multi-gigabit plastic optical fibre link. An FPGA-based 1.5 Gbit/s error free transmission over 50 m standard SI-POF using CAP64 is achieved, providing 2.9 dB power margin without forward error correction. © 2012 OSA.

Orthogonal multipulse modulation in optical datacommunications

Optical datacommunication links are now required at rates beyond 40 Gb/s. Achieving robust low-cost transmission at these rates necessitates consideration of advanced modulation formats. This paper concentrates on schemes using multiple orthogonal pulses and outlines the advantages relative to alternatives such as multilevel modulation. Recent real-time experimental results at 56 Gb/s are described. © 2013 IEEE.

Orthogonal multipulse modulation for 64 gigabit fibre channel

Real-time orthogonal multipulse modulation is demonstrated at 56 Gb/s with transmission over 500 m of single-mode fiber. Up to 2 dBo power budget advantage is predicted relative to alternatives such as PAM4. © 2013 OSA.

3 Gbit/s LED-based step index plastic optical fiber link using multilevel pulse amplitude modulation

Multilevel PAM is investigated for a LED-based SI-POF link. Using PAM-8, transmission at a record 3 Gbit/s is demonstrated for a maximum length of 25 m step index POF with offline post-receiver processing. © 2013 OSA.

100 Gigabit ethernet transmission enabled by carrierless amplitude and phase modulation using QAM receivers

Simulations have investigated single laser 100G Ethernet links enabled by CAP-16 using QAM receivers that not only lower significantly system timing jitter sensitivity but also outperform PAM and standard CAP in terms of power margin. © 2013 OSA.

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. © OSA 2012.

Improved exponents and rates for bit-interleaved coded modulation

Mismatched decoding theory is applied to study the error exponents (both random-coding and expurgated) and achievable rates for bit-interleaved coded modulation (BICM). The gains achieved by constant-composition codes with respect to the the usual random codes are highlighted. © 2013 IEEE.

Micro-electro-mechanical resonant tilt sensor with 250 nano-radian resolution

This paper reports a high-resolution frequency-output MEMS tilt sensor based on resonant sensing principles. The tilt sensor measures orientation by sensing the component of gravitational acceleration along a specified input axis. A combination of design enhancements enables significantly higher sensitivity for this device as compared to previously reported prototype sensors. The MEMS tilt sensor is calibrated on a manual tilt table over tilt angles ranging over 0-90 degrees with a relatively linear response measured in the range of ±20°(linearity error <2.3%) with a scale factor of approximately 50.06 Hz/degree. The noise-limited resolution of the sensor is found to be approximately 250 nano-radians for an integration time of 0.8 s, which is over an order of magnitude better than previously reported results [1]. © 2013 IEEE.