Data compression by linear prediction for storage and transmission of EEG signals

The EEG time series has been subjected to various formalisms of analysis to extract meaningful information regarding the underlying neural events. In this paper the linear prediction (LP) method has been used for analysis and presentation of spectral array data for the better visualisation of background EEG activity. It has also been used for signal generation, efficient data storage and transmission of EEG. The LP method is compared with the standard Fourier method of compressed spectral array (CSA) of the multichannel EEG data. The autocorrelation autoregressive (AR) technique is used for obtaining the LP coefficients with a model order of 15. While the Fourier method reduces the data only by half, the LP method just requires the storage of signal variance and LP coefficients. The signal generated using white Gaussian noise as the input to the LP filter has a high correlation coefficient of 0.97 with that of original signal, thus making LP as a useful tool for storage and transmission of EEG. The biological significance of Fourier method and the LP method in respect to the microstructure of neuronal events in the generation of EEG is discussed.

Decorrelation of broad band signals by toeplitz-block-toeplitz structuring

We propose F-norm of the cross-correlation part of the array covariance matrix as a measure of correlation between the impinging signals and study the performance of different decorrelation methods in the broadband case using this measure. We first show that dimensionality of the composite signal subspace, defined as the number of significant eigenvectors of the source sample covariance matrix, collapses in the presence of multipath and the spatial smoothing recovers this dimensionality. Using an upper bound on the proposed measure, we then study the decorrelation of the broadband signals with spatial smoothing and the effect of spacing and directions of the sources on the rate of decorrelation with progressive smoothing. Next, we introduce a weighted smoothing method based on Toeplitz-block-Toeplitz (TBT) structuring of the data covariance matrix which decorrelates the signals much faster than the spatial smoothing. Computer simulations are included to demonstrate the performance of the two methods.

Blind separation of multiple co-channel BPSK signals arriving at an antenna array

In this letter, we propose a method for blind separation of d co-channel BPSK signals arriving at an antenna array. Our method involves two steps. In the first step, the received data vectors at the output of the array is grouped into 2d clusters. In the second step, we assign the 2d d-tuples with ±1 elements to these clusters in a consistent fashion. From the knowledge of the cluster to which a data vector belongs, we estimate the bits transmitted at that instant. Computer simulations are used to study the performance of our method

Computing Fractal Dimension of Signals using Multiresolution Box-counting Method

In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are provided to demonstrate the performance of the proposed method using parametric fractal signals. The estimation accuracy of the method is compared with that of Katz, Sevcik, and Higuchi methods. In ddition, some properties of the FD are discussed.

Thermally Controlled Cyclic Insertion/Ejection of Dopant Ions and Reversible Zinc Blende/Wurtzite Phase Changes in ZnS Nanostructures

We report a reversible phase transformation of platelet-shaped ZnS nanostructures between wurtzite (WZ) and zinc blende (ZB) phases by reversible insertion/ ejection of dopant Mn(II) ions induced by a thermocyclic process. In a reaction flask loaded with WZ ZnS platelets and Mn molecular precursors, during heating Mn ions are incorporated and change the phase of the host nanostructures to ZB; during cooling Mn ions are spontaneously ejected, returning the host nanoplatelets to the original WZ phase. These reversible changes are monitored for several cycles with PL, EPR, XRD, and HRTEM. Interestingly, the (0001) WZ platelets transform to (110) ZB following a nucleation and growth process triggered by a local increase/depletion of the Mn2+ concentration in the nanocrystals.

Thermally Controlled Cyclic Insertion/Ejection of Dopant Ions and Reversible Zinc Blende/Wurtzite Phase Changes in ZnS Nanostructures

We report a reversible phase transformation of platelet-shaped ZnS nanostructures between wurtzite (WZ) and zinc blende (ZB) phases by reversible insertion/ ejection of dopant Mn(II) ions induced by a thermocyclic process. In a reaction flask loaded with WZ ZnS platelets and Mn molecular precursors, during heating Mn ions are incorporated and change the phase of the host nanostructures to ZB; during cooling Mn ions are spontaneously ejected, returning the host nanoplatelets to the original WZ phase. These reversible changes are monitored for several cycles with PL, EPR, XRD, and HRTEM. Interestingly, the (0001) WZ platelets transform to (110) ZB following a nucleation and growth process triggered by a local increase/depletion of the Mn2+ concentration in the nanocrystals.

Secretion of endocrine signals by the primate embryo during the peri-implantation period

Development of preimplantation embryos and blastocyst implantation are critical early events in the establishment of pregnancy. In primates, embryonic signals, secreted during the peri-implantation period, are believed to play a major role in the regulation of embryonic differentiation and implantation. However, only limited progress has been made in the molecular and functional characterization of embryonic signals, partly due to severe paucity of primate embryos and the lack of optimal culture conditions to obtain viable embryo development. Two embryonic (endocrine) secretions, i.e. chorionic gonadotrophin (CG) and gonadotrophin releasing hormone (GnRH) are being studied. This article reviews the current status of knowledge on the recovery and culture of embryos, their secretion of CG, GnRH and other potential endocrine signals and their regulation and physiological role(s) during the peri-implantation period in primates, including humans.

Gas-phase controlled mass transfer in a foam-bed reactor

Gas-phase controlled absorption of ammonia in foams made of solutions of sulphuric acid has been studied experimentally. Effects of gas-phase concentration of ammonia and type of surfactant on the performance of the foam-bed reactor are investigated. Gas-phase controlled absorption from a spherical bubble is anaylzed using the asymptotic value of Sherwood number (Sh = 6.58), for both negligible as well as significant changes in the volume of the bubble. The experimental data are shown to be in good agreement with the single-stage model of the foam-bed reactor using these asymptotic sub-models, as well as the diffusion-in-sphere analysis available in literature. Influence of effective diffusivity on the time dependence of fractional gas absorption has been found to be unimportant for foam columns with large times of contact. The asymptotic sub-models have been compared and use of the rigid-sphere asymptotic sub-model is recommended for foam columns of practical relevence.

Use of finite wordlength FIR digital filter structures with improved magnitude and phase characteristics for reduction of muscle noise in EEG signals

One of the main disturbances in EEG signals is EMG artefacts generated by muscle movements. In the paper, the use of a linear phase FIR digital low-pass filter with finite wordlength precision coefficients is proposed, designed using the compensation procedure, to minimise EMG artefacts in contaminated EEG signals. To make the filtering more effective, different structures are used, i.e. cascading, twicing and sharpening (apart from simple low-pass filtering) of the designed FIR filter Modifications are proposed to twicing and sharpening structures to regain the linear phase characteristics that are lost in conventional twicing and sharpening operations. The efficacy of all these transformed filters in minimising EMG artefacts is studied, using SNR improvements as a performance measure for simulated signals. Time plots of the signals are also compared. Studies show that the modified sharpening structure is superior in performance to all other proposed methods. These algorithms have also been applied to real or recorded EMG-contaminated EEG signal. Comparison of time plots, and also the output SNR, show that the proposed modified sharpened structure works better in minimising EMG artefacts compared with other methods considered.

Controlled synthesis of CuO nanostructures on Cu foil, rod and grid

CuO nanowires are synthesized by heating Cu foil, rod and grid in ambient without employing a catalyst or gas flow at temperatures ranging from 400 to 800 degrees C for a duration of 1-12 h. Scanning electron microscopy (SEM) investigation reveals the formation of nanowires. The structure, morphology and phase of the as-synthesized nanowires are analyzed by various techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR). It is found that these nanowires are composed of CuO phase and the underlying film is of Cu2O. A systematic study is carried out to find the possibilities for the transformation of one phase to another completely. A possible growth mechanism for the nanowires is also discussed. (C) 2011 Elsevier B.V. All rights reserved.

Amorphous, Monoclinic, and Tetragonal Porous Zirconia Through a Controlled Self-Sustained Combustion Route

Porous, large surface area, metastable zirconias, are of importance to catalytic, electrochemical, biological, and thermal insulation applications. Combustion synthesis is a very commonly used method for producing such zirconias. However, its rapid nature makes control difficult. A simple modification has been made to traditional solution combustion synthesis to address this problem. It involves the addition of starch to yield a starting mixture with a ``dough-like'' consistency. Just 5 wt% starch is seen to significantly alter the combustion characteristics of the ``dough.'' In particular, it helps to achieve better control over reaction zone temperature that is significantly lower than the one calculated by the adiabatic approximation typically used in self-propagating high-temperature synthesis. The effect of such control is demonstrated by the ability to tune dough composition to yield zirconias with different phase compositions from the relatively elusive ``amorphous'' to monoclinic (> 30 nm grain size) and tetragonal pure zirconia (< 30 nm grain size). The nature of this amorphous phase has been investigated using infrared spectroscopy. Starch content also helps tailor porosity in the final product. Zirconias with an average pore size of about 50 mu m and specific surface area as large as 110 m2/g have been obtained.

Unusual charged Higgs boson signals at CERN LEP 2

We have made a detailed study of the signals expected at CERN LEP 2 from charged scalar bosons whose dominant decay channels are into four fermions. The event rates as well as kinematics of the final states are discussed when such scalars are either pair produced or are generated through a tree-level interaction involving a charged scalar, the W, and the Z. The backgrounds in both cases are discussed. We also suggest the possibility of reconstructing the mass of such a scalar at LEP 2.

Nonlinear dynamics and chaotic motions in feedback-controlled two- and three-degree-of-freedom robots

The dynamics of a feedback-controlled rigid robot is most commonly described by a set of nonlinear ordinary differential equations. In this paper we analyze these equations, representing the feedback-controlled motion of two- and three-degrees-of-freedom rigid robots with revolute (R) and prismatic (P) joints in the absence of compliance, friction, and potential energy, for the possibility of chaotic motions. We first study the unforced or inertial motions of the robots, and show that when the Gaussian or Riemannian curvature of the configuration space of a robot is negative, the robot equations can exhibit chaos. If the curvature is zero or positive, then the robot equations cannot exhibit chaos. We show that among the two-degrees-of-freedom robots, the PP and the PR robot have zero Gaussian curvature while the RP and RR robots have negative Gaussian curvatures. For the three-degrees-of-freedom robots, we analyze the two well-known RRP and RRR configurations of the Stanford arm and the PUMA manipulator respectively, and derive the conditions for negative curvature and possible chaotic motions. The criteria of negative curvature cannot be used for the forced or feedback-controlled motions. For the forced motion, we resort to the well-known numerical techniques and compute chaos maps, Poincare maps, and bifurcation diagrams. Numerical results are presented for the two-degrees-of-freedom RP and RR robots, and we show that these robot equations can exhibit chaos for low controller gains and for large underestimated models. From the bifurcation diagrams, the route to chaos appears to be through period doubling.

Noise and outlier removal from jet engine health signals using weighted FIR median hybrid filters

The removal of noise and outliers from measurement signals is a major problem in jet engine health monitoring. Topical measurement signals found in most jet engines include low rotor speed, high rotor speed. fuel flow and exhaust gas temperature. Deviations in these measurements from a baseline 'good' engine are often called measurement deltas and the health signals used for fault detection, isolation, trending and data mining. Linear filters such as the FIR moving average filter and IIR exponential average filter are used in the industry to remove noise and outliers from the jet engine measurement deltas. However, the use of linear filters can lead to loss of critical features in the signal that can contain information about maintenance and repair events that could be used by fault isolation algorithms to determine engine condition or by data mining algorithms to learn valuable patterns in the data, Non-linear filters such as the median and weighted median hybrid filters offer the opportunity to remove noise and gross outliers from signals while preserving features. In this study. a comparison of traditional linear filters popular in the jet engine industry is made with the median filter and the subfilter weighted FIR median hybrid (SWFMH) filter. Results using simulated data with implanted faults shows that the SWFMH filter results in a noise reduction of over 60 per cent compared to only 20 per cent for FIR filters and 30 per cent for IIR filters. Preprocessing jet engine health signals using the SWFMH filter would greatly improve the accuracy of diagnostic systems. (C) 2002 Published by Elsevier Science Ltd.

Defining the ‘modified Griffin plot’ in vortex-induced vibration: revealing the effect of Reynolds number using controlled damping

In the present work, we study the transverse vortex-induced vibrations of an elastically mounted rigid cylinder in a fluid flow. We employ a technique to accurately control the structural damping, enabling the system to take on both negative and positive damping. This permits a systematic study of the effects of system mass and damping on the peak vibration response. Previous experiments over the last 30 years indicate a large scatter in peak-amplitude data ($A^*$) versus the product of mass–damping ($\alpha$), in the so-called ‘Griffin plot’. A principal result in the present work is the discovery that the data collapse very well if one takes into account the effect of Reynolds number ($\mbox{\textit{Re}}$), as an extra parameter in a modified Griffin plot. Peak amplitudes corresponding to zero damping ($A^*_{{\alpha}{=}0}$), for a compilation of experiments over a wide range of $\mbox{\textit{Re}}\,{=}\,500-33000$, are very well represented by the functional form $A^*_{\alpha{=}0} \,{=}\, f(\mbox{\textit{Re}}) \,{=}\, \log(0.41\,\mbox{\textit{Re}}^{0.36}$). For a given $\mbox{\textit{Re}}$, the amplitude $A^*$ appears to be proportional to a function of mass–damping, $A^*\propto g(\alpha)$, which is a similar function over all $\mbox{\textit{Re}}$. A good best-fit for a wide range of mass–damping and Reynolds number is thus given by the following simple expression, where $A^*\,{=}\, g(\alpha)\,f(\mbox{\textit{Re}})$: \[ A^* \,{=}\,(1 - 1.12\,\alpha + 0.30\,\alpha^2)\,\log (0.41\,\mbox{\textit{Re}}^{0.36}). \] In essence, by using a renormalized parameter, which we define as the ‘modified amplitude’, $A^*_M\,{=}\,A^*/A^*_{\alpha{=}0}$, the previously scattered data collapse very well onto a single curve, $g(\alpha)$, on what we refer to as the ‘modified Griffin plot’. There has also been much debate over the last three decades concerning the validity of using the product of mass and damping (such as $\alpha$) in these problems. Our results indicate that the combined mass–damping parameter ($\alpha$) does indeed collapse peak-amplitude data well, at a given $\mbox{\textit{Re}}$, independent of the precise mass and damping values, for mass ratios down to $m^*\,{=}\,1$.