The capacity and attractor basins of associative memory models

The original publication is available at www.springerlink.com . Copyright SpringerThe performance characteristics of five variants of the Hopfield network are examined. Two performance metrics are used: memory capacity, and a measure of the size of basins of attraction. We find that the posttraining adjustment of processor thresholds has, at best, little or no effect on performance, and at worst a significant negative effect. The adoption of a local learning rule can, however, give rise to significant performance gains.Peer reviewe

SyntenyVista

Visualization of genome comparisons is an important research tool in biology, medicine and agricultural research. We present a new visualization system, SyntenyVista, which allows for interactive exploration of genome comparisons. It incorporates a novel feature called cartoon scaling designed to improve the user's ability to understand gene relationships. SyntenyVista is being deployed in the context of e-Science where it will provide an entry point to integrated data on genomes, animal models of disease, and disease genes

Feedback control of unsupported standing in paraplegia. Part I: optimal control approach

This is the first of a pair of papers which describe an investigation into the feasibility of providing artificial balance to paraplegics using electrical stimulation of the paralyzed muscles. By bracing the body above the shanks, only stimulation of the plantarflexors is necessary. This arrangement prevents any influence from the intact neuromuscular system above the spinal cord lesion. Here, the authors extend the design of the controllers to a nested-loop LQG (linear quadratic Gaussian) stimulation controller which has ankle moment feedback (inner loops) and inverted pendulum angle feedback (outer loop). Each control loop is tuned by two parameters, the control weighting and an observer rise-time, which together determine the behavior. The nested structure was chosen because it is robust, despite changes in the muscle properties (fatigue) and interference from spasticity

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

A randomised controlled pilot study: the effectiveness of narrative exposure therapy with adult survivors of the Sichuan earthquake

Background: Post-Traumatic Stress Disorder (PTSD) is a common psychological reaction after large-scale natural disasters. Given the number of people involved and shortage of resources in any major disaster, brief, pragmatic and easily trainable interventions are needed. The aim of this study is to evaluate the efficacy of Narrative Exposure Therapy (NET) as a short-term treatment for PTSD using Chinese earthquake survivors. Methods: A randomized waiting-list control pilot study was conducted between December 2009 and March 2010, at the site of the Sichuan earthquake in Beichuan County, China. Adult participants with newly diagnosed Post Traumatic Stress Disorder (PTSD) were randomly allocated to Narrative Exposure Therapy (NET) or a Waiting-List (WL) condition. The latter received NET treatment after a two-week waiting period. To compare the effectiveness of NET in traumatised earthquake survivors, both groups were assessed on PTSD symptoms, general mental health, anxiety and depression, social support, coping style and posttraumatic change before and after treatment and two months post treatment. Results: Adult participants (n=22) were randomly allocated to receive NET (n=11) or WL (n=11). Twenty two participants (11 in NET group, 11 in WL) were included in the analysis of primary outcomes. Compared with WL, NET showed significant reductions in PTSD symptoms, anxiety and depression, general mental stress and increased posttraumatic growth. The WL group later showed similar improvements after treatment. These changes remained stable for a two-month follow-up. Measures of social support and coping showed no stable effects. Conclusions: NET is effective in treating post-earthquake traumatic symptoms in adult Chinese earthquake survivors. The findings help advance current knowledge in the management of PTSD after natural disasters and inform future research. Larger sample sizes are needed to extend the present findings

Adjustment of a turbulent boundary layer to a 'canopy' of roughness elements

A model is developed for the adjustment of the spatially averaged time-mean flow of a deep turbulent boundary layer over small roughness elements to a canopy of larger three-dimensional roughness elements. Scaling arguments identify three stages of the adjustment. First, the drag and the finite volumes of the canopy elements decelerate air parcels; the associated pressure gradient decelerates the flow within an impact region upwind of the canopy. Secondly, within an adjustment region of length of order Lc downwind of the leading edge of the canopy, the flow within the canopy decelerates substantially until it comes into a local balance between downward transport of momentum by turbulent stresses and removal of momentum by the drag of the canopy elements. The adjustment length, Lc, is proportional to (i) the reciprocal of the roughness density (defined to be the frontal area of canopy elements per unit floor area) and (ii) the drag coefficient of individual canopy elements. Further downstream, within a roughness-change region, the canopy is shown to affect the flow above as if it were a change in roughness length, leading to the development of an internal boundary layer. A quantitative model for the adjustment of the flow is developed by calculating analytically small perturbations to a logarithmic turbulent velocity profile induced by the drag due to a sparse canopy with L/Lc≪1, where L is the length of the canopy. These linearized solutions are then evaluated numerically with a nonlinear correction to account for the drag varying with the velocity. A further correction is derived to account for the finite volume of the canopy elements. The calculations are shown to agree with experimental measurements in a fine-scale vegetation canopy, when the drag is more important than the finite volume effects, and a canopy of coarse-scale cuboids, when the finite volume effects are of comparable importance to the drag in the impact region. An expression is derived showing how the effective roughness length of the canopy, \z0eff, is related to the drag in the canopy. The value of \z0eff varies smoothly with fetch through the adjustment region from the roughness length of the upstream surface to the equilibrium roughness length of the canopy. Hence, the analysis shows how to resolve the unphysical flow singularities obtained with previous models of flow over sudden changes in surface roughness

High performance associative memory models and weight dilution

The consequences of diluting the weights of the standard Hopfield architecture associative memory model, trained using perceptron like learning rules, is examined. A proportion of the weights of the network are removed; this can be done in a symmetric and asymmetric way and both methods are investigated. This paper reports experimental investigations into the consequences of dilution in terms of: capacity, training times and size of basins of attraction. It is concluded that these networks maintain a reasonable performance at fairly high dilution rates.Final Accepted Versio

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

Feedback control of unsupported standing in paraplegia. Part II: experimental results

For pt. I see ibid., vol. 5, no. 4, p. 331-40 (1997). This is the second of a pair of papers which describe an investigation into the feasibility of providing artificial balance to paraplegics using electrical stimulation of the paralyzed muscles. By bracing the body above the shanks, only stimulation of the plantar flexors is necessary. This arrangement prevents any influence from the intact neuromuscular system above the spinal cord lesion. Here, the authors present experimental results from intact and paraplegic subjects

Feedback control of unsupported standing

This paper presents the results of continuing work on feedback control of unsupported standing in paraplegia. Our experimental setup considers a situation in which all joints above the ankle are braced, and stabilising torque at the ankle is generated by stimulation of the plantarflexors. A previous study showed that short periods of unsupported standing with paraplegic subjects could be achieved. In order to improve consistency and reliability of unsupported standing we are currently investigating several modifications to the control strategy. The paper reports progress towards this goal