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End date: 2009 × Start date: 2000 × DDC: 530 × Has files: Yes × Type: Text × Publisher: Göttingen : Copernicus ×

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Now showing 1 - 4 of 4
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    Statistical characteristics of surrogate data based on geophysical measurements
    (Göttingen : Copernicus, 2006) Venema, V.; Bachner, S.; Rust, H.W.; Simmer, C.
    In this study, the statistical properties of a range of measurements are compared with those of their surrogate time series. Seven different records are studied, amongst others, historical time series of mean daily temperature, daily rain sums and runoff from two rivers, and cloud measurements. Seven different algorithms are used to generate the surrogate time series. The best-known method is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm, which is able to reproduce the measured distribution as well as the power spectrum. Using this setup, the measurements and their surrogates are compared with respect to their power spectrum, increment distribution, structure functions, annual percentiles and return values. It is found that the surrogates that reproduce the power spectrum and the distribution of the measurements are able to closely match the increment distributions and the structure functions of the measurements, but this often does not hold for surrogates that only mimic the power spectrum of the measurement. However, even the best performing surrogates do not have asymmetric increment distributions, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found deviations of the structure functions on small scales.
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    A propagation-separation approach to estimate the autocorrelation in a time-series
    (Göttingen : Copernicus, 2008) Divine, D.V.; Polzehl, J.; Godtliebsen, F.
    The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.
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    An integrated 3.1-5.1 GHz pulse generator for ultra-wideband wireless localization systems
    (Göttingen : Copernicus, 2006) Fan, X.; Fischer, G.; Dietrich, B.
    This paper presents an implementation of an integrated Ultra-wideband (UWB), Binary-Phase Shift Keying (BPSK) Gaussian modulated pulse generator. VCO, multiplier and passive Gaussian filter are the key components. The VCO provides the carrier frequency of 4.1 GHz, the LC Gaussian filter is responsible for the pulse shaping in the baseband. Multiplying the baseband pulse and the VCO frequency shifts the pulse to the desired center frequency. The generated Gaussian pulse ocupppies the frequency range from 3.1 to 5.1 GHz with the center frequency at 4.1 GHz. Simulations and measured results show that this spectrum fulfills the mask for indoor communication systems given by the FCC (Federal Communications Commission, 2002). The total power consumption is 55 mW using a supply voltage of 2.5 V. Circuits are realized using the IHP 0.25 μm SiGe:C BiCMOS technology.
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    Phase noise and jitter modeling for fractional-N PLLs
    (Göttingen : Copernicus, 2007) Osmany, S.A.; Herzel, F.; Schmalz, K.; Winkler, W.
    We present an analytical phase noise model for fractional-N phase-locked loops (PLL) with emphasis on integrated RF synthesizers in the GHz range. The noise of the crystal reference, the voltage-controlled oscillator (VCO), the loop filter, the charge pump, and the sigma-delta modulator (SDM) is filtered by the PLL operation. We express the rms phase error (jitter) in terms of phase noise of the reference, the VCO phase noise and the third-order loop filter parameters. In addition, we consider OFDM systems, where the PLL phase noise is reduced by digital signal processing after down-conversion of the RF signal to baseband. The rms phase error is discussed as a function of the loop parameters. Our model drastically simplifies the noise optimization of the PLL loop dynamics.