Input window size and neural network predictors

Neural network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results from dynamic systems theory are briefly introduced, and heuristics for finding the correct embedding dimension, and hence window size, are discussed. The method is applied to two time series and the resulting generalisation performance of the trained feedforward neural network predictors is analysed. It is shown that the heuristics can provide useful information in defining the appropriate network architectur

High Performance Associative Memories and Structured Weight Dilution

Copyright SpringerThe consequences of two techniques for symmetrically diluting the weights of the standard Hopfield architecture associative memory model, trained using a non-Hebbian learning rule, are examined. This paper reports experimental investigations into the effect of dilution on factors such as: pattern stability and attractor performance. It is concluded that these networks maintain a reasonable level of performance at fairly high dilution rates

Global and Feature Based Gender Classification of Faces: A Comparison of Human Performance and Computational Models

Original paper can be found at: http://eproceedings.worldscinet.com/9789812701886/9789812701886_0036.html Copyright World Scientific Publishing Company. http://dx.doi.org/10.1142/9789812701886_0036Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and feature based representation of face images that includes both global and featural information. We use dimensionality reduction techniques and a support vector machine classifier and show that this method performs better than either global or feature based representations alone.Peer reviewe

A neural network model of visual object recognition impairment after brain damage

Dysfunction of the visual object recognition system in humans is briefly discussed and a basic connectionist model of visual object recognition is introduced. Experimentation in which two variants of this model are lesioned is undertaken. The results suggest that the well documented phenomenon of superordinate preservation is model independent. Differential category specific recognition deficits are also observed in this model, however these are sensitive to each particular variant

The Role of Global and Feature Based Information in Gender Classification of Faces: A Comparison of Human Performance and Computational Models

Peer reviewe

The BCS Critical Temperature in a Weak External Electric Field via a Linear Two-Body Operator

We study the critical temperature of a superconductive material in a weak external electric potential via a linear approximation of the BCS functional. We reproduce a similar result as in Frank et al. (Commun Math Phys 342(1):189–216, 2016, [5]) using the strategy introduced in Frank et al. (The BCS critical temperature in a weak homogeneous magnetic field, [2]), where we considered the case of an external constant magnetic field

The BCS critical temperature in a weak external electric field via a linear two-body operator

We study the critical temperature of a superconductive material in a weak external electric potential via a linear approximation of the BCS functional. We reproduce a similar result as in [Frank, Hainzl, Seiringer, Solovej, 2016] using the strategy introduced in [Frank, Hainzl, Langmann, 2018], where we considered the case of an external constant magnetic field.Comment: Dedicated to Herbert Spohn on the occasion of his seventieth birthday; 29 page

Gender classification of face images: the role of global and feature-based information

Peer reviewe

Buoyant Venus station mission feasibility study for 1972 and 1973 launch opportunities. Volume 1 - Mission summary definition and comparison Final report

Mission planning, scheduling, and costs for 1972 and 1973 buoyant Venus station missio

Superburst oscillations: ocean and crustal modes excited by Carbon-triggered Type I X-ray bursts

Accreting neutron stars (NS) can exhibit high frequency modulations in their lightcurves during thermonuclear X-ray bursts, known as burst oscillations. The frequencies can be offset from the spin frequency of the NS by several Hz, and can drift by 1-3 Hz. One possible explanation is a mode in the bursting ocean, the frequency of which would decrease (in the rotating frame) as the burst cools, hence explaining the drifts. Most burst oscillations have been observed during H/He triggered bursts, however there has been one observation of oscillations during a superburst; hours' long Type I X-ray bursts caused by unstable carbon burning deeper in the ocean. This paper calculates the frequency evolution of an oceanic r-mode during a superburst. The rotating frame frequency varies during the burst from 4-14 Hz, and is sensitive to the background parameters, in particular the temperature of the ocean and ignition depth. This calculation is compared to the superburst oscillations observed on 4U-1636-536. The predicted mode frequencies ($\sim$ 10 Hz) would require a spin frequency of $\sim$ 592 Hz to match observations; 6 Hz higher than the spin inferred from an oceanic r-mode model for the H/He triggered burst oscillations. This model also over-predicts the frequency drift during the superburst by 90 %.Comment: Accepted for publication in MNRA