Selection of proposal distributions for generalized importance sampling estimators

The standard importance sampling (IS) estimator, generally does not work well in examples involving simultaneous inference on several targets as the importance weights can take arbitrarily large values making the estimator highly unstable. In such situations, alternative generalized IS estimators involving samples from multiple proposal distributions are preferred. Just like the standard IS, the success of these multiple IS estimators crucially depends on the choice of the proposal distributions. The selection of these proposal distributions is the focus of this article. We propose three methods based on (i) a geometric space filling coverage criterion, (ii) a minimax variance approach, and (iii) a maximum entropy approach. The first two methods are applicable to any multi-proposal IS estimator, whereas the third approach is described in the context of Doss's (2010) two-stage IS estimator. For the first method we propose a suitable measure of coverage based on the symmetric Kullback-Leibler divergence, while the second and third approaches use estimates of asymptotic variances of Doss's (2010) IS estimator and Geyer's (1994) reverse logistic estimator, respectively. Thus, we provide consistent spectral variance estimators for these asymptotic variances. The proposed methods for selecting proposal densities are illustrated using various detailed examples

M-ary phase-shift keying using finite impulse response filter based on window function method

Digital filters are vastly utilized in the area of communication. A perfect digital filter efficiency is significant and hence to design a digital finite impulse response filter (FIR) favorable all the wanted situations is necessary. In this paper, a new proposed FIR digital filter designed, the fineness of the submitted filter is tested in terms of BER and then matched with another window, namely Hamming, Hanning, and Blackman. The design procedure done in the MATLAB software. It is concluded that the Blackman window is the best window to design the FIR digital filter, because it is bit error rate is better than another window

Time-frequency methods for coherent spectroscopy

Time-frequency decomposition techniques, borrowed from the signal-processing field, have been adapted and applied to the analysis of 2D oscillating signals. While the Fourier-analysis techniques available so far are able to interpret the information content of the oscillating signal only in terms of its frequency components, the time-frequency transforms (TFT) proposed in this work can instead provide simultaneously frequency and time resolution, unveiling the dynamics of the relevant beating components, and supplying a valuable help in their interpretation. In order to fully exploit the potentiality of this method, several TFTs have been tested in the analysis of sample 2D data. Possible artifacts and sources of misinterpretation have been identified and discussed

Sidelobe Suppression in Pulse Compresssed Radar Signal

Radio Detection And Ranging, RADAR, is a system that is used to detect and track a target at distant location with its other features (like velocity, direction etc.). The system uses various techniques to enhance its efficiency in terms of different physical parameters. Pulse compression technique provides the radar designers with an ability to combine the benefits of low power transmitters and the larger pulse wavelength to maintain the energy content of the pulse, in turn, the process elevates the range detection ability of high duration pulses and the resolution capacity of short pulses. To enhance the bandwidth of the high duration pulses so that better range resolution capability can be achieved, modulation in frequency and phase is done. Frequency or phase modulation is employed to a long duration pulse before it is transmitted and the received pulse is then passed through a filter to get its energy accumulated into a short pulse. Usually, matched filter is a common choice for pulse compression. Due to the high sidelobe peaks associated with the mainlobe in the matched filter output, which is simply an ACF of the input pulse, they have the possibility of masking the weaker targets near the stronger ones. So, the high sidelobes are needed to be suppressed to avoid such circumstances. Normally, the matched filter output has the sidelobe level of -13.5dB which can be improved by the use of the techniques like adaptive filtering, weighting through the use of windows etc. The windowing technique, besides suppressing the sidelobe also reduces the SNR which leads to reduction in rate of false alarm rate. A stepped frequency train of LFM pulses is an efficient method to enhance the overall bandwidth of the signal and maintaining the instantaneous bandwidth at the same time. But they are associated with the ambiguous peaks whose peak value is similar to the mainlobe peak and are also known as the grating lobes which have the potential of masking the smaller targets. So, it becomes necessary to suppress or nullify them by proper adjustment of the design parameters.

Design of Fir Digital Bandpass Filter with Hamming Window and Hanning Window Method for Fetal Doppler

DESIGN OF FIR DIGITAL BANDPASS FILTER WITH HAMMING WINDOW AND HANNING WINDOW METHOD FOR FETAL DOPPLE

Identification of open cracks using wavelet analysis

Damage detection in flexural members by wavelet analysis involves certain important factors such as the choice of wavelet function, the effects of windowing and the effects of masking due to the presence of noise during measurement. A numerical study has been performed in this paper addressing these issues for a beam element with an open crack. The first natural modeshape of a beam with an open crack has been simulated. Gaussian white noise has been synthetically introduced to the simulated modeshape and the onset of masking has been studied. A wavelet based method of damage detection can be useful in the identification of damaged bridge structures and is applicable under the presence of measurement noise as well

On the use of time and correlation windows for non-parametric spectral analysis

Design of time and correlation windows for non-parametric frequency response estimates. The thesis deals with problems that arise in the field of spectral analysis due to finite observations of input and output records. In particular, it is concerned with the method of applying time and correlation windows in spectral analysis procedures to obtain non- parametric frequency response estimates of open-loop time invariant systems. The thesis reviews and develops the sources of error that arise when frequency response techniques are applied directly to windowed records of input and output data to estimate the frequency response of open loop systems. Having identified the cause of these errors, methods of eliminating or reducing them are studied. The techniques introduced, which are believed to be novel, involve the use of differing time windows for the input and output data records. Rather than the use of previously developed and ad-hoc symmetrical windows, it is shown that windows can be designed on the basis of some specified criterion such as maximum square coherence or minimum mean square error. Another method of window selection is based on minimum a priori knowledge of the system characteristics which leads to further improvement in the frequency response estimates. These Least Mean Square Error Windows, are solved numerically and are shown to be superior to conventional, classical windows developed in the past. Window carpentry and modelling of power spectral data Careful mathematical modelling is always required in the design of modern suspension bridges, as these models are used to predict free vibrations and excitation responses. However, in order to validate any assumption made in the modelling and accuracy of the model parameters, full scale testing procedures need to be undertaken. From the spectrum of measured ambient responses of such large structures, it is necessary to determine the damping factor, resonant frequency and amplitude for each resonance. Such high Q systems have very sharp spectral peaks and any smoothing; by splitting into segments or by smoothing over frequencies of estimates obtained from a single realisation, removes important fine spectral details. By analysis and experiment, tests on known similar models show that least squares fitting on the windowed unsmoothed estimates reduces bias in the spectral estimates. It is also be shown that least squares fitting on the unsmoothed cumulative spectra further reduces this bias. Both procedures, applied to ambient response data from the Humber suspension bridge, are found to differ consistently from earlier results. In particular estimates of damping factor are shown to be very much smaller than those based on smoothed spectral density measurements