Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Aplicação de modelos de informação condicionada na avaliação do desempenho de fundos de investimento mobiliário em Portugal: a selectividade e o market timing (análise diária vs. análise mensal

Dissertação de mest., Finanças Empresariais, Faculdade de Economia, Univ. do Algarve, 2010

Timing and mode of delivery in twins : the ongoing controversy

Tese de doutoramento, Medicina (Ginecologia e Obstetrícia), Universidade de Lisboa, Faculdade de Medicina, 2014

Mass-wasting episodes in the geological evolution of the Azores islands : timing, recurrence, mechanisms and consequence

Tese de doutoramento (co-tutela), Geologia (Geodinâmica Interna), Faculdade de Ciências da Universidade de Lisboa, Faculté des Sciences D’Orsay-Université Paris-Sud, 2014

Pollen Season and Climate: Is the Timing of Birch Pollen Release in the UK Approaching its Limit?

In light of heightened interest in the response of pollen phenology to temperature, we investigated recent changes to the onset of Betula (birch) pollen seasons in central and southern England, including a test of predicted advancement of the Betula pollen season for London. We calculated onset of birch pollen seasons using daily airborne pollen data obtained at London, Plymouth and Worcester, determined trends in the start of the pollen season and compared timing of the birch pollen season with observed temperature patterns for the period 1995–2010. We found no overall change in the onset of birch pollen in the study period although there was evidence that the response to temperature was nonlinear and that a lower asymptotic start of the pollen season may exist. The start of the birch pollen season was strongly correlated with March mean temperature. These results reinforce previous findings showing that the timing of the birch pollen season in the UK is particularly sensitive to spring temperatures. The climate relationship shown here persists over both longer decadal-scale trends and shorter, seasonal trends as well as during periods of ‘sign-switching’ when cooler spring temperatures result in later start dates. These attributes, combined with the wide geographical coverage of airborne pollen monitoring sites, some with records extending back several decades, provide a powerful tool for the detection of climate change impacts, although local site factors and the requirement for winter chilling may be confounding factors.

Narrow-band variable center frequency single-loop and multistage sigma-delta modulators for bandpass signals

Oversampled narrow-band single-loop and multistage resonator-based bandpass sigma-delta (Σ-Δ) modulators that can accommodate different passband center to sampling frequency ratios are reported. These tunable bandpass configurations are designed by analytically determining and subsequently verifying through detailed empirical simulations the required compensation hardware to deliver enhanced noise-shaping. It is demonstrated that comparatively superior in-band signal-to-noise ratios and dynamic ranges are attributed to the inclusion of appropriate digital feedforward and feedback compensators within these structures.

Variable centre frequency resonator based bandpass Σ-Δ modulator

A novel resonator-based bandpass Σ-Δ modulator with an in-built variable centre frequency feature is presented. This structure is designed by analytically determining and subsequently verifying through behavioural level simulations the necessary compensation hardware to be placed in the feedback to ensure stability and good dynamic range performance.

Post awakening salivary cortisol secretion and trait well-being: The importance of sample timing accuracy

Indices of post awakening cortisol secretion (PACS), include the rise in cortisol(cortisol awakening response: CAR) and overall cortisol concentrations (e.g. area under the curve with reference to ground: AUCg) in the first 30—45 min. Both are commonly investigated in relation to psychosocial variables. Although sampling within the domestic setting is ecologically valid, participant non-adherence to the required timing protocol results in erroneous measurement of PACS and this may explain discrepancies in the literature linking these measures to trait well-being (TWB). We have previously shown that delays of little over 5 min(between awakening and the start of sampling) to result in erroneous CAR estimates. In this study, we report for the first time on the negative impact of sample timing inaccuracy (verified by electronic-monitoring) on the efficacy to detect significant relationships between PACS and TWB when measured in the domestic setting.Healthy females (N = 49, 20.5 ± 2.8 years) selected for differences in TWB collected saliva samples (S1—4) on 4 days at 0, 15, 30, 45 min post awakening, to determine PACS. Adherence to the sampling protocol was objectively monitored using a combination of electronic estimates of awakening (actigraphy) and sampling times (track caps).Relationships between PACS and TWB were found to depend on sample timing accuracy. Lower TWB was associated with higher post awakening cortisol AUCg in proportion to the mean sample timing accuracy (p < .005). There was no association between TWB and the CAR even taking into account sample timing accuracy. These results highlight the importance of careful electronic monitoring of participant adherence for measurement of PACS in the domestic setting. Mean sample timing inaccuracy, mainly associated with delays of >5 min between awakening and collection of sample 1 (median = 8 min delay), negatively impacts on the sensitivity of analysis to detect associations between PACS and TWB.

Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems

Power converters play a vital role in the integration of wind power into the electrical grid. Variable-speed wind turbine generator systems have a considerable interest of application for grid connection at constant frequency. In this paper, comprehensive simulation studies are carried out with three power converter topologies: matrix, two-level and multilevel. A fractional-order control strategy is studied for the variable-speed operation of wind turbine generator systems. The studies are in order to compare power converter topologies and control strategies. The studies reveal that the multilevel converter and the proposed fractional-order control strategy enable an improvement in the power quality, in comparison with the other power converters using a classical integer-order control strategy. (C) 2010 Elsevier Ltd. All rights reserved.

Transient analysis of variable-speed wind turbines at wind speed disturbances and a pitch control malfunction

As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

A framework for the development of parallel and distributed real-time embedded systems

Embedded real-time applications increasingly present high computation requirements, which need to be completed within specific deadlines, but that present highly variable patterns, depending on the set of data available in a determined instant. The current trend to provide parallel processing in the embedded domain allows providing higher processing power; however, it does not address the variability in the processing pattern. Dimensioning each device for its worst-case scenario implies lower average utilization, and increased available, but unusable, processing in the overall system. A solution for this problem is to extend the parallel execution of the applications, allowing networked nodes to distribute the workload, on peak situations, to neighbour nodes. In this context, this report proposes a framework to develop parallel and distributed real-time embedded applications, transparently using OpenMP and Message Passing Interface (MPI), within a programming model based on OpenMP. The technical report also devises an integrated timing model, which enables the structured reasoning on the timing behaviour of these hybrid architectures.

Fractional order modelling of zero length column desorption response for adsorbents with variable particle sizes

This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.

The effect of fractional order in variable structure control

This paper studies fractional variable structure controllers. Two cases are considered namely, the sliding reference model and the control action, that are generalized from integer into fractional orders. The test bed consists in a mechanical manipulator and the effect of the fractional approach upon the system performance is evaluated. The results show that fractional dynamics, both in the switching surface and the control law are important design algorithms in variable structure controllers.