Quaternary surface-water stable isotope signal from calcareous nannofossils at DSDP Site 90-593, South Tasman Sea

Oxygen isotope values from calcareous nannofossils in four cores spanning the Quaternary from DSDP Site 593 in Tasman Sea are compared with the delta18O signal of planktonic and benthic foraminifers from the same samples. The classic mid-late Quaternary isotope stages are exhibited with stage 12 particularly well developed. When delta18O values of nannofossils are adjusted for coccolithophore vital effects they indicate larger (by 1-6°C) surface to bottom paleotemperature gradients and greater (by 1-3°C) changes in mean sea-surface temperature between full glacial and interglacial conditions than do delta18O values from planktonic foraminifers. Along with the foraminifers, the nannofossils record a bimodal distribution of delta18O between the early and mid-late Quaternary, indicating a significant change in global ice budget. The delta13C of nannofossils also shows a bimodal distribution, but is opposite to that for the foraminifers. Nannofossil delta18O values record a shift of c. -0.8? at isotope stage 8 corresponding to a major reduction in abundance of the previously dominant gephyrocapsids. A shift in delta13C of c. -1.5? also occurs at stage 8, and a shift in delta13C of c. +1.2? at around stage 14. The delta18O shift in nannofossils is at least a Pacific-wide phenomenon; the delta13C shifts are possibly global. The delta13C signal of nannofossils exhibits an antipathetic relationship to that of benthic foraminifers back to isotope stage 18 but no significant correlation beyond this level to the base of the Quaternary. This is interpreted as reflecting local productivity dominating global influences on delta13C since stage 18 at DSDP Site 593. The difference between nannofossil and benthic foraminifer delta13C signals (Delta13C) tends to be maximum during glacial stages and minimum during interglacials throughout the section, showing a strong correlation with the nannofossil delta180 signal. The increased partitioning of 13C between surface and bottom waters during the glacial periods may indicate heightened productivity in surface waters in the southern Tasman Sea at these times.

Novel method to improve the signal-to-noise ratio in the far-field results obtained from planar near-field measurements

A method to reduce the noise power in far-field pattern without modifying the desired signal is proposed. Therefore, an important signal-to-noise ratio improvement may be achieved. The method is used when the antenna measurement is performed in planar near-field, where the recorded data are assumed to be corrupted with white Gaussian and space-stationary noise, because of the receiver additive noise. Back-propagating the measured field from the scan plane to the antenna under test (AUT) plane, the noise remains white Gaussian and space-stationary, whereas the desired field is theoretically concentrated in the aperture antenna. Thanks to this fact, a spatial filtering may be applied, cancelling the field which is located out of the AUT dimensions and which is only composed by noise. Next, a planar field to far-field transformation is carried out, achieving a great improvement compared to the pattern obtained directly from the measurement. To verify the effectiveness of the method, two examples will be presented using both simulated and measured near-field data.

Area-Efficient Linear Regression Architecture for Real-Time Signal Processing on FPGAs

Linear regression is a technique widely used in digital signal processing. It consists on finding the linear function that better fits a given set of samples. This paper proposes different hardware architectures for the implementation of the linear regression method on FPGAs, specially targeting area restrictive systems. It saves area at the cost of constraining the lengths of the input signal to some fixed values. We have implemented the proposed scheme in an Automatic Modulation Classifier, meeting the hard real-time constraints this kind of systems have.

Optical signal processing with electrooptic modulators and dispersion

A review of the main techniques that have been proposed for temporal processing of optical pulses that are the counterpart of the well-known spatial arrangements will be presented. They are translated to the temporal domain via the space-time duality and implemented with electrooptical phase and amplitude modulators and dispersive devices. We will introduce new variations of the conventional approaches and we will focus on their application to optical communications systems

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.