Sparse Bayesian Nonlinear System Identification using Variational Inference

IEEE Bayesian nonlinear system identification for one of the major classes of dynamic model, the nonlinear autoregressive with exogenous input (NARX) model, has not been widely studied to date. Markov chain Monte Carlo (MCMC) methods have been developed, which tend to be accurate but can also be slow to converge. In this contribution, we present a novel, computationally efficient solution to sparse Bayesian identification of the NARX model using variational inference, which is orders of magnitude faster than MCMC methods. A sparsity-inducing hyper-prior is used to solve the structure detection problem. Key results include: 1. successful demonstration of the method on low signal-to-noise ratio signals (down to 2dB); 2. successful benchmarking in terms of speed and accuracy against a number of other algorithms: Bayesian LASSO, reversible jump MCMC, forward regression orthogonalisation, LASSO and simulation error minimisation with pruning; 3. accurate identification of a real world system, an electroactive polymer; and 4. demonstration for the first time of numerically propagating the estimated nonlinear time-domain model parameter uncertainty into the frequency-domain

Sparse Bayesian Nonlinear System Identification using Variational Inference

IEEE Bayesian nonlinear system identification for one of the major classes of dynamic model, the nonlinear autoregressive with exogenous input (NARX) model, has not been widely studied to date. Markov chain Monte Carlo (MCMC) methods have been developed, which tend to be accurate but can also be slow to converge. In this contribution, we present a novel, computationally efficient solution to sparse Bayesian identification of the NARX model using variational inference, which is orders of magnitude faster than MCMC methods. A sparsity-inducing hyper-prior is used to solve the structure detection problem. Key results include: 1. successful demonstration of the method on low signal-to-noise ratio signals (down to 2dB); 2. successful benchmarking in terms of speed and accuracy against a number of other algorithms: Bayesian LASSO, reversible jump MCMC, forward regression orthogonalisation, LASSO and simulation error minimisation with pruning; 3. accurate identification of a real world system, an electroactive polymer; and 4. demonstration for the first time of numerically propagating the estimated nonlinear time-domain model parameter uncertainty into the frequency-domain

Frequency-domain analysis for nonlinear systems with time-domain model parameter uncertainty

Frequency-domain analysis of dynamic systems is important across many areas of engineering. However, whilst there are many analysis methods for linear systems, the problem is much less widely studied for nonlinear systems. Frequency-domain analysis of nonlinear systems using frequency response functions (FRFs) is particularly important to reveal resonances, super/sub-harmonics and energy transfer across frequencies. In this paper the novel contribution is a time-domain model-based approach to describing the uncertainty of nonlinear systems in the frequency-domain. The method takes a nonlinear input-output model that has normally distributed parameters, and propagates that uncertainty into the frequency-domain using analytic expressions based on FRFs. We demonstrate the approach on both synthetic examples of nonlinear systems and a real-world nonlinear system identified from experimental data. We benchmark the proposed approach against a brute-force technique based on Monte Carlo sampling and show that there is good agreement between the methods

Optimized quantum nondemolition measurement of a field quadrature

We suggest an interferometric scheme assisted by squeezing and linear feedback to realize the whole class of field-quadrature quantum nondemolition measurements, from Von Neumann projective measurement to fully non-destructive non-informative one. In our setup, the signal under investigation is mixed with a squeezed probe in an interferometer and, at the output, one of the two modes is revealed through homodyne detection. The second beam is then amplitude-modulated according to the outcome of the measurement, and finally squeezed according to the transmittivity of the interferometer. Using strongly squeezed or anti-squeezed probes respectively, one achieves either a projective measurement, i.e. homodyne statistics arbitrarily close to the intrinsic quadrature distribution of the signal, and conditional outputs approaching the corresponding eigenstates, or fully non-destructive one, characterized by an almost uniform homodyne statistics, and by an output state arbitrarily close to the input signal. By varying the squeezing between these two extremes, or simply by tuning the internal phase-shift of the interferometer, the whole set of intermediate cases can also be obtained. In particular, an optimal quantum nondemolition measurement of quadrature can be achieved, which minimizes the information gain versus state disturbance trade-off

Simulations of cubic-tetragonal ferroelastics

We study domain patterns in cubic-tetragonal ferroelastics by solving numerically equations of motion derived from a Landau model of the phase transition, including dissipative stresses. Our system sizes, of up to 256^3 points, are large enough to reveal many structures observed experimentally. Most patterns found at late stages in the relaxation are multiply banded; all three tetragonal variants appear, but inequivalently. Two of the variants form broad primary bands; the third intrudes into the others to form narrow secondary bands with the hosts. On colliding with walls between the primary variants, the third either terminates or forms a chevron. The multipy banded patterns, with the two domain sizes, the chevrons and the terminations, are seen in the microscopy of zirconia and other cubic-tetragonal ferroelastics. We examine also transient structures obtained much earlier in the relaxation; these show the above features and others also observed in experiment.Comment: 7 pages, 6 colour figures not embedded in text. Major revisions in conten

Geospatial analysis and living urban geometry

This essay outlines how to incorporate morphological rules within the exigencies of our technological age. We propose using the current evolution of GIS (Geographical Information Systems) technologies beyond their original representational domain, towards predictive and dynamic spatial models that help in constructing the new discipline of "urban seeding". We condemn the high-rise tower block as an unsuitable typology for a living city, and propose to re-establish human-scale urban fabric that resembles the traditional city. Pedestrian presence, density, and movement all reveal that open space between modernist buildings is not urban at all, but neither is the open space found in today's sprawling suburbs. True urban space contains and encourages pedestrian interactions, and has to be designed and built according to specific rules. The opposition between traditional self-organized versus modernist planned cities challenges the very core of the urban planning discipline. Planning has to be re-framed from being a tool creating a fixed future to become a visionary adaptive tool of dynamic states in evolution

2015 ACVIM Small Animal Consensus Statement on Seizure Management in Dogs

This report represents a scientific and working clinical consensus statement on seizure management in dogs based on current literature and clinical expertise. The goal was to establish guidelines for a predetermined, concise, and logical sequential approach to chronic seizure management starting with seizure identification and diagnosis (not included in this report), reviewing decision‐making, treatment strategies, focusing on issues related to chronic antiepileptic drug treatment response and monitoring, and guidelines to enhance patient response and quality of life. Ultimately, we hope to provide a foundation for ongoing and future clinical epilepsy research in veterinary medicine

The effect of carbohydrate ingestion on the motor skill proficiency of soccer players

This study examined the effects of ingesting a glucose-polymer (GP) solution on the motor skill proficiencies of association football (soccer) players from two teams playing during two matches in a cool environment. Fifteen minutes before each match and at halftime, players from both teams ingested 5 ml/kg of either placebo or a 6.9% GP solution. GP ingestion did not improve tackling, heading, dribbling, or shooting ability. On the contrary, the mean of successful tackles was lower with GP ingestion than with placebo. The success rate for heading, dribbling, and shooting also tended to be lower in the GP than in the placebo condition. In contrast, success in passing and ball control was similar in the two conditions. Improvements in passing and ball control may have been related to a decrease in the intensity of play in the second half of the game. These data indicate that there are no measurable benefits of GP ingestion for the motor skill proficiencies of soccer players during games played in a cool environment.IS

Jamming at Zero Temperature and Zero Applied Stress: the Epitome of Disorder

We have studied how 2- and 3- dimensional systems made up of particles interacting with finite range, repulsive potentials jam (i.e., develop a yield stress in a disordered state) at zero temperature and applied stress. For each configuration, there is a unique jamming threshold, $\phi_c$, at which particles can no longer avoid each other and the bulk and shear moduli simultaneously become non-zero. The distribution of $\phi_c$ values becomes narrower as the system size increases, so that essentially all configurations jam at the same $\phi$ in the thermodynamic limit. This packing fraction corresponds to the previously measured value for random close-packing. In fact, our results provide a well-defined meaning for "random close-packing" in terms of the fraction of all phase space with inherent structures that jam. The jamming threshold, Point J, occurring at zero temperature and applied stress and at the random close-packing density, has properties reminiscent of an ordinary critical point. As Point J is approached from higher packing fractions, power-law scaling is found for many quantities. Moreover, near Point J, certain quantities no longer self-average, suggesting the existence of a length scale that diverges at J. However, Point J also differs from an ordinary critical point: the scaling exponents do not depend on dimension but do depend on the interparticle potential. Finally, as Point J is approached from high packing fractions, the density of vibrational states develops a large excess of low-frequency modes. All of these results suggest that Point J may control behavior in its vicinity-perhaps even at the glass transition.Comment: 21 pages, 20 figure