Performance Evaluation of Adaptive H-infinity Filter

This study is related to the use of adaptive H-infinity filter  for multi sensor data fusion ( based tracking. AHIF can work efficiently in the presence of uncertainties using sliding window concept. In the present use of , the length of window size is varied to eliminate/minimize the estimation errors and predict almost precise location of a target. Simulation experiments are conducted to evaluate performance of  in comparison with Kalman and H-Infinity filters for mild and evasive maneuvering targets.  Performs better in terms location accuracy and position fit error

Fuzzy Logic Applications in Filtering and Fusion for Target Tracking

A fuzzy Kalman filter algorithm is developed for target tracking applications and itsperformance evaluated using several numerical examples. The approach is relatively novel. Acomparison with Kalman filter and an adaptive tuning algorithm is carried out. The applicabilityand usefulness of fuzzy logic in data fusion is also demonstrated. The performance of both theextended Kalman filter and fuzzy extended Kalman filter is evaluated using real data of amanoeuvering target and it is found that fuzzy extended Kalman filter shows better performanceas compared to extended Kalman filter

Estimation Methods for Determination of Drag Characteristics of Fly-by-Wire Aircraft

"In this paper, several parameter/state estimation approaches for the determination of drag polars from flight data are described and evaluated for a fly-by-wire (FBW) aircraft. Both model-based approaches (MBAs) and non-model-based approaches (NMBAs) are considered. Dynamic response data from roller coaster and wind- up-turn manoeuvres are generated in a FBW aircraft flight simulator at different flight conditions and the typical performance results are presented. A novel approach to estimate the drag polar has been evaluated. It has been found that the NMBAs perform better than the MBAs. Classically, the MBAs have been used for the determination of drag polars. The merits of an NMBA are that it does not require specification of the detailed model of the aerodynamic coefficients and it can be suitably used for online estimation of drag polars from the flight data of aerospace vehicle

Spontaneously opening GABA receptors play a significant role in neuronal signal filtering and integration

Acknowledgements This work was supported by The Rosetrees Trust Research Grant A1066, RS MacDonald Seedcorn Award and Wellcome Trust—UoE ISSF Award to S.S. The authors thank Prof. David Wyllie (University of Edinburgh) and Prof. Dmitri Rusakov (UCL) for their valuable suggestions on paper preparation.Peer reviewedPublisher PD

Progress in gene therapy for neurological disorders

Diseases of the nervous system have devastating effects and are widely distributed among the population, being especially prevalent in the elderly. These diseases are often caused by inherited genetic mutations that result in abnormal nervous system development, neurodegeneration, or impaired neuronal function. Other causes of neurological diseases include genetic and epigenetic changes induced by environmental insults, injury, disease-related events or inflammatory processes. Standard medical and surgical practice has not proved effective in curing or treating these diseases, and appropriate pharmaceuticals do not exist or are insufficient to slow disease progression. Gene therapy is emerging as a powerful approach with potential to treat and even cure some of the most common diseases of the nervous system. Gene therapy for neurological diseases has been made possible through progress in understanding the underlying disease mechanisms, particularly those involving sensory neurons, and also by improvement of gene vector design, therapeutic gene selection, and methods of delivery. Progress in the field has renewed our optimism for gene therapy as a treatment modality that can be used by neurologists, ophthalmologists and neurosurgeons. In this Review, we describe the promising gene therapy strategies that have the potential to treat patients with neurological diseases and discuss prospects for future development of gene therapy

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

View the PDF document PC Based Flight Path Reconstruction Using UD Factorisation Filtering Algorithm .

The results of flight path reconstruction using UD factorisation-based Kalman filtering algorithm are presented. The algorithm was implemented using PC-MATLAB functions and validated for simulated as well as real flight data. It is of considerable relevance to analysis of aircraft accident data and general flight data for aerospace vehicles