Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

A Maximum-Likelihood Interpretation for Slow Feature Analysis

The brain extracts useful features from a maelstrom of sensory information, and a fundamental goal of theoretical neuroscience is to work out how it does so. One proposed feature extraction strategy is motivated by the observation that the meaning of sensory data, such as the identity of a moving visual object, is often more persistent than the activation of any single sensory receptor. This notion is embodied in the slow feature analysis (SFA) algorithm, which uses “slowness” as an heuristic by which to extract semantic information from multi-dimensional time-series. Here, we develop a probabilistic interpretation of this algorithm showing that inference and learning in the limiting case of a suitable probabilistic model yield exactly the results of SFA. Similar equivalences have proved useful in interpreting and extending comparable algorithms such as independent component analysis. For SFA, we use the equivalent probabilistic model as a conceptual spring-board, with which to motivate several novel extensions to the algorithm.

Flame interactions in turbulent premixed twin V-flames

Multiple flame-flame interactions in premixed combustion are investigated using direct numerical simulations of twin turbulent V-flames for a range of turbulence intensities and length scales. Interactions are identified using a novel automatic feature extraction (AFE) technique, based on data registration using the dual-tree complex wavelet transform. Information on the time, position, and type of interactions, and their influence on the flame area is extracted using AFE. Characteristic length and time scales for the interactions are identified. The effect of interactions on the flame brush is quantified through a global stretch rate, defined as the sum of flamelet stretch and interaction stretch contributions. The effects of each interaction type are discussed. It is found that the magnitude of the fluctuations in flamelet and interaction stretch are comparable, and a qualitative sensitivity to turbulence length scale is found for one interaction type. Implications for modeling are discussed. © 2013 Copyright Taylor and Francis Group, LLC.

The effects of non-unity lewis numbers on turbulent premixed flame interactions in a twin V-flame configuration

The influence of Lewis number on turbulent premixed flame interactions is investigated using automatic feature extraction (AFE) applied to high-resolution flame simulation data. Premixed turbulent twin V-flames under identical turbulence conditions are simulated at global Lewis numbers of 0.4, 0.8, 1.0, and 1.2. Information on the position, frequency, and magnitude of the interactions is compared, and the sensitivity of the results to sample interval is discussed. It is found that both the frequency and magnitude of normal type interactions increases with decreasing Lewis number. Counternormal type interactions become more likely as the Lewis number increases. The variation in both the frequency and the magnitude of the interactions is found to be caused by large-scale changes in flame wrinkling resulting from differences in the thermo-diffusive stability of the flames. During flame interactions, thermo-diffusive effects are found to be insignificant due to the separation of time scales. © 2013 Copyright Taylor and Francis Group, LLC.

Material parameter extraction in THz-TDS using a converging beam transfer function

We demonstrate a parameter extraction algorithm based on a theoretical transfer function, which takes into account a converging THz beam. Using this, we successfully extract material parameters from data obtained for a quartz sample with a THz time domain spectrometer. © 2010 IEEE.

Direct parameter extraction in capacitively transduced micromechanical resonators using the anti-resonance

This paper presents a method for the fast and direct extraction of model parameters for capacitive MEMS resonators from their measured transmission response such as quality factor, resonant frequency, and motional resistance. We show that these parameters may be extracted without having to first de-embed the resonator motional current from the feedthrough. The series and parallel resonances from the measured electrical transmission are used to determine the MEMS resonator circuit parameters. The theoretical basis for the method is elucidated by using both the Nyquist and susceptance frequency response plots, and applicable in the limit where CF > CmQ; commonly the case when characterizing MEMS resonators at RF. The method is then applied to the measured electrical transmission for capacitively transduced MEMS resonators, and compared against parameters obtained using a Lorentzian fit to the measured response. Close agreement between the two methods is reported herein. © 2010 IEEE.

Carbon onions: Carriers of the 217.5 nm interstellar absorption feature

The UV-VIS characteristics of carbon ions fabricated by an arch discharge in water or liquid nitrogen show characteristics that are similar to the interstellar absorption feature. Thus, high purity and well separated carbon onion samples prepared by annealing the as-fabricated powder in air at 600°C for 60 showed a constant absorption peak at 4.6 μm-1 with a variable width ranging from 1.2-1.6 μm-1. In addition to the UV-VIS data, the origin of the absorption feature at 4.6 μm-1 in carbon onions can be attributed to the collective excitations of π plasmons.

Direct parameter extraction in feedthrough-embedded capacitive MEMS resonators

This paper presents a method for fast and accurate determination of parameters relevant to the characterization of capacitive MEMS resonators like quality factor (Q), resonant frequency (fn), and equivalent circuit parameters such as the motional capacitance (Cm). In the presence of a parasitic feedthrough capacitor (CF) appearing across the input and output ports, the transmission characteristic is marked by two resonances: series (S) and parallel (P). Close approximations of these circuit parameters are obtained without having to first de-embed the resonator motional current typically buried in feedthrough by using the series and parallel resonances. While previous methods with the same objective are well known, we show that these are limited to the condition where CF ≪ CmQ. In contrast, this work focuses on moderate capacitive feedthrough levels where CF > CmQ, which are more common in MEMS resonators. The method is applied to data obtained from the measured electrical transmission of fabricated SOI MEMS resonators. Parameter values deduced via direct extraction are then compared against those obtained by a full extraction procedure where de-embedding is first performed and followed by a Lorentzian fit to the data based on the classical transfer function associated with a generic LRC series resonant circuit. © 2011 Elsevier B.V. All rights reserved.