Ten thousand times faster: Classifying multidimensional data on a spiking neuromorphic hardware system.

Discrimination of sensory inputs is a computational task that biological neuronal systems perform very efficiently. Assessing the principles in those systems is a promising approach to develop technical solutions for many problems, such as data classification. A particular problem here is to train a classifier in a supervised fashion to discriminate classes in multidimensional data. We implemented a network of spiking neurons that solves this task using a neuromorphic hardware system, that is, analog neuronal circuits on a silicon substrate. This system enables us to do high-performance computation in a biologically inspired way, with spiking neurons as computational units. In this contribution, we illustrate solutions to technical challenges that occur when implementing a classifier on neuromorphic hardware. 

The network topology of the insect olfactory system provides a well suited template for a neuronal architecture processing multidimensional data. In our classifier network, the value of each dimension of a data vector determines the rate of a stochastically generated spike train. The spike trains are fed into non-overlapping populations of neurons. Those populations project onto an association layer with winner-take-all properties representing the output of the classifier. During classifier training, the weights in this projection are adjusted according to a firing-rate based learning rule. 

The values in multidimensional data sets are typically real numbers, but neuronal firing rates are restricted to values between zero and some maximal value. Hence, the data must be transformed into a positive, bounded representation. We achieved this by representing each data point as a vector of distances to a number of points in data space (“virtual receptors” [1]). The representation by virtual receptors inevitably introduces correlation between input dimensions. We reduced this correlation using lateral inhibition in the first neuronal layer, leading to a significant increase in classifier performance. We found that decorrelation was most efficient when we scaled the inhibitory weights according to the correlation between the connected populations. 

We ran our classifier network on a neuromorphic hardware system that runs at ten thousand times the speed of biological neurons, thus suited for high performance computing [2]. However, the considerable variance of rate-response sensitivity across hardware neurons decreased classification performance. We therefore developed a calibration routine to counteract the neuronal variance.

References

[1] Schmuker, M. and Schneider, G. (2007). Processing and classification of chemical data inspired by insect olfaction. Proc. Natl. Acad. Sci. U S A 104, 20285-20289. 
[2] Brüderle, D., Bill, J., Kaplan, B., Kremkow, J., Meier, K., Müller, E. and Schemmel, J. (2010). Simulator-like exploration of cortical network architectures with a mixed-signal VLSi system. In Proc. of IEEE Intern. Symp. on Circuits and Systems (ISCAS), 2784–8787

A comparison of short-term marking methods for small frogs using a model species, the striped marsh frog (Limnodynastes peronii)

We compared three methods of marking individual small frogs for identification in short-term studies (several days) using a model species, Limnodynastes peronii (the striped marsh frog). We performed a manipulative experiment under laboratory conditions to compare retention times of gentian violet, mercurochrome and powdered fluorescent pigment. Gentian violet produced the most durable marks with retention times between two and four days. Mercurochrome was retained for at least one day by all treated frogs. Fluorescent pigment was either not retained at all or for one day at most, which suggests that this marking method may not be reliable for short-term studies where identification is required. No adverse reactions to any of the marking methods were detected in our study. Our findings indicate that gentian violet represents a promising alternative as a minimally invasive marking technique for studies of small frogs requiring only shortterm retention of identification marks

A predictive framework and review of the ecological impacts of exotic plant invasions on reptiles and amphibians

The invasive spread of exotic plants in native vegetation can pose serious threats to native faunal assemblages. This is of particular concern for reptiles and amphibians because they form a significant component of the world's vertebrate fauna, play a pivotal role in ecosystem functioning and are often neglected in biodiversity research. A framework to predict how exotic plant invasion will affect reptile and amphibian assemblages is imperative for conservation, management and the identification of research priorities. Here, we present a new predictive framework that integrates three mechanistic models. These models are based on exotic plant invasion altering: (1) habitat structure; (2) herbivory and predator-prey interactions; (3) the reproductive success of reptile and amphibian species and assemblages. We present a series of testable predictions from these models that arise from the interplay over time among three exotic plant traits (growth form, area of coverage, taxonomic distinctiveness) and six traits of reptiles and amphibians (body size, lifespan, home range size, habitat specialisation, diet, reproductive strategy). A literature review provided robust empirical evidence of exotic plant impacts on reptiles and amphibians from each of the three model mechanisms. Evidence relating to the role of body size and diet was less clear-cut, indicating the need for further research. The literature provided limited empirical support for many of the other model predictions. This was not, however, because findings contradicted our model predictions but because research in this area is sparse. In particular, the small number of studies specifically examining the effects of exotic plants on amphibians highlights the pressing need for quantitative research in this area. There is enormous scope for detailed empirical investigation of interactions between exotic plants and reptile and amphibian species and assemblages. The framework presented here and further testing of predictions will provide a basis for informing and prioritising environmental management and exotic plant control efforts. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society

The demand for sports and exercise: Results from an illustrative survey

Funding from the Department of Health policy research programme was used in this study.There is a paucity of empirical evidence on the extent to which price and perceived benefits affect the level of participation in sports and exercise. Using an illustrative sample of 60 adults at Brunel University, West London, we investigate the determinants of demand for sports and exercise. The data were collected through face-to-face interviews that covered indicators of sports and exercise behaviour; money/time price and perceived benefits of participation; and socio- economic/demographic details. Count, linear and probit regression models were fitted as appropriate. Seventy eight per cent of the sample participated in sports and exercise and spent an average of £27 per month and an average of 20 min travelling per occasion of sports and exercise. The demand for sport and exercise was negatively associated with time (travel or access time) and ‘variable’ price and positively correlated with ‘fixed’ price. Demand was price inelastic, except in the case of meeting the UK government’s recommended level of participation, which is time price elastic (elasticity = −2.2). The implications of data from a larger nationally representative sample as well as the role of economic incentives in influencing uptake of sports and exercise are discussed.This article is available through the Brunel Open Access Publishing Fund

Towards a Time-predictable Dual-Issue Microprocessor: The Patmos Approach

Current processors are optimized for average case performance, often leading to a high worst-case execution time (WCET). Many architectural features that increase the average case performance are hard to be modeled for the WCET analysis. In this paper we present Patmos, a processor optimized for low WCET bounds rather than high average case performance. Patmos is a dual-issue, statically scheduled RISC processor. The instruction cache is organized as a method cache and the data cache is organized as a split cache in order to simplify the cache WCET analysis. To fill the dual-issue pipeline with enough useful instructions, Patmos relies on a customized compiler. The compiler also plays a central role in optimizing the application for the WCET instead of average case performance

ADC Nonlinearity Correction for the Majorana Demonstrator

Imperfections in analog-to-digital conversion (ADC) cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the Majorana Demonstrator 76Ge neutrinoless double-beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearities. A simple measurement protocol was developed that did not require sophisticated equipment or lengthy data-taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearities by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value

Roy-Steiner equations for pion-nucleon scattering

Starting from hyperbolic dispersion relations, we derive a closed system of Roy-Steiner equations for pion-nucleon scattering that respects analyticity, unitarity, and crossing symmetry. We work out analytically all kernel functions and unitarity relations required for the lowest partial waves. In order to suppress the dependence on the high-energy regime we also consider once- and twice-subtracted versions of the equations, where we identify the subtraction constants with subthreshold parameters. Assuming Mandelstam analyticity we determine the maximal range of validity of these equations. As a first step towards the solution of the full system we cast the equations for the $\pi\pi\to\bar NN$ partial waves into the form of a Muskhelishvili-Omn\`es problem with finite matching point, which we solve numerically in the single-channel approximation. We investigate in detail the role of individual contributions to our solutions and discuss some consequences for the spectral functions of the nucleon electromagnetic form factors.Comment: 106 pages, 18 figures; version published in JHE

Solving the mu problem with a heavy Higgs boson

We discuss the generation of the mu-term in a class of supersymmetric models characterized by a low energy effective superpotential containing a term lambda S H_1 H_2 with a large coupling lambda~2. These models generically predict a lightest Higgs boson well above the LEP limit of 114 GeV and have been shown to be compatible with the unification of gauge couplings. Here we discuss a specific example where the superpotential has no dimensionful parameters and we point out the relation between the generated mu-term and the mass of the lightest Higgs boson. We discuss the fine-tuning of the model and we find that the generation of a phenomenologically viable mu-term fits very well with a heavy lightest Higgs boson and a low degree of fine-tuning. We discuss experimental constraints from collider direct searches, precision data, thermal relic dark matter abundance, and WIMP searches finding that the most natural region of the parameter space is still allowed by current experiments. We analyse bounds on the masses of the superpartners coming from Naturalness arguments and discuss the main signatures of the model for the LHC and future WIMP searches.Comment: Extended discussion of the LHC phenomenology, as published on JHEP plus an addendum on the existence of further extremal points of the potential. 47 pages, 16 figure

Analysis of factors influencing the ultrasonic fetal weight estimation

Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation