Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr – Part 2: A new reconstruction of the interplanetary magnetic field

We present a new reconstruction of the interplanetary magnetic field (IMF, B) for 1846–2012 with a full analysis of errors, based on the homogeneously constructed IDV(1d)composite of geomagnetic activity presented in Part 1 (Lockwood et al., 2013a). Analysis of the dependence of the commonly used geomagnetic indices on solar wind parameters is presented which helps explain why annual means of interdiurnal range data, such as the new composite, depend only on the IMF with only a very weak influence of the solar wind flow speed. The best results are obtained using a polynomial (rather than a linear) fit of the form B = χ · (IDV(1d) − β)α with best-fit coefficients χ = 3.469, β = 1.393 nT, and α = 0.420. The results are contrasted with the reconstruction of the IMF since 1835 by Svalgaard and Cliver (2010).

Interaction among non-toxic phytoplankton, toxic phytoplankton and zooplankton: inferences from field observations

We explore the mutual dependencies and interactions among different groups of species of the plankton population, based on an analysis of the long-term field observations carried out by our group in the North–West coast of the Bay of Bengal. The plankton community is structured into three groups of species, namely, non-toxic phytoplankton (NTP), toxic phytoplankton (TPP) and zooplankton. To find the pair-wise dependencies among the three groups of plankton, Pearson and partial correlation coefficients are calculated. To explore the simultaneous interaction among all the three groups, a time series analysis is performed. Following an Expectation Maximization (E-M) algorithm, those data points which are missing due to irregularities in sampling are estimated, and with the completed data set a Vector Auto-Regressive (VAR) model is analyzed. The overall analysis demonstrates that toxin-producing phytoplankton play two distinct roles: the inhibition on consumption of toxic substances reduces the abundance of zooplankton, and the toxic materials released by TPP significantly compensate for the competitive disadvantages among phytoplankton species. Our study suggests that the presence of TPP might be a possible cause for the generation of a complex interaction among the large number of phytoplankton and zooplankton species that might be responsible for the prolonged coexistence of the plankton species in a fluctuating biomass.

Interplanetary magnetic field control of dayside auroral activity and the transfer of momentum across the dayside magnetopause

The orientation of the Interplanetary Magnetic Field (IMF) during transient bursts of ionospheric flow and auroral activity in the dayside auroral ionosphere is studied, using data from the EISCAT radar, meridian-scanning photometers, and an all-sky TV camera, in conjunction with simultaneous observations of the interplanetary medium by the IMP-8 satellite. It is found that the ionospheric flow and auroral burst events occur regularly (mean repetition period equal to 8.3 ± 0.6 min) during an initial period of about 45 min when the IMF is continuously and strongly southward in GSM coordinates, consistent with previous observations of the occurrence of transient dayside auroral activity. However, in the subsequent 1.5 h, the IMF was predominantly northward, and only made brief excursions to a southward orientation. During this period, the mean interval between events increased to 19.2 ± 1.7 min. If it is assumed that changes in the North-South component of the IMF are aligned with the IMF vector in the ecliptic plane, the delays can be estimated between such a change impinging upon IMP-8 and the response in the cleft ionosphere within the radar field-of-view. It is found that, to within the accuracy of this computed lag, each transient ionospheric event during the period of predominantly northward IMF can be associated with a brief, isolated southward excursion of the IMF, as observed by IMP-8. From this limited period of data, we therefore suggest that transient momentum exchange between the magnetosheath and the ionosphere occurs quasi-periodically when the IMF is continuously southward, with a mean period which is strikingly similar to that for Flux Transfer Events (FTEs) at the magnetopause. During periods of otherwise northward IMF, individual momentum transfer events can be triggered by brief swings to southward IMF. Hence under the latter conditions the periodicity of the events can reflect a periodicity in the IMF, but that period will always be larger than the minimum value which occurs when the IMF is strongly and continuously southward.