Pulse Duration Distribution Research Articles

FRACTAL PROPERTIES OF MICROPLASMA BREAKDOWN AND STRUCTURAL HETEROGENEITY OF SEMICONDUCTOR MATERIALS

This work presents experimental results on the study of current-voltage characteristics and oscillograms of microplasma pulses of the p-n-junction avalanche breakdown. Based on the latter, the pulse duration distributions are determined. As a result, it is shown that microplasma noise has fractal properties. The latter form the basis of avalanche breakdown types developed classification. The correlation between the fractal dimension of microplasma noise and structural inhomogeneities of functional semiconductor structures is revealed.

Auto-correlation function and frequency spectrum due to a super-position of uncorrelated exponential pulses

The auto-correlation function and the frequency power spectral density due to a super-position of uncorrelated exponential pulses are considered. These are shown to be independent of the degree of pulse overlap and thereby the intermittency of the stochastic process. For constant pulse duration and a one-sided exponential pulse shape, the power spectral density has a Lorentzian shape which is flat for low frequencies and a power law at high frequencies. The algebraic tail is demonstrated to result from the discontinuity in the pulse function. For a strongly asymmetric two-sided exponential pulse shape, the frequency spectrum is a broken power law with two scaling regions. In the case of a symmetric pulse shape, the power spectral density is the square of a Lorentzian function. The steep algebraic tail at high frequencies in these cases is demonstrated to follow from the discontinuity in the derivative of the pulse function. A random distribution of pulse durations is shown to result in apparently longer correlation times but has no influence on the asymptotic power law tail of the frequency spectrum. The effect of additional random noise is also discussed, leading to a flat spectrum for high frequencies. The probability density function for the fluctuations is shown to be independent of the distribution of pulse durations. The predictions of this model describe the variety of auto-correlation functions and power spectral densities reported from experimental measurements in the scrape-off layer of magnetically confined plasmas.

Power law spectra and intermittent fluctuations due to uncorrelated Lorentzian pulses

A stochastic model for intermittent fluctuations due to a super-position of uncorrelated Lorentzian pulses is presented. For a constant pulse duration, this is shown to result in an exponential power spectral density for the stationary process. A random distribution of pulse durations modifies the frequency spectrum, and several examples are shown to result in power law spectra. The distribution of pulse durations does not influence the characteristic function and thus neither the moments nor the probability density function of the random variable. It is demonstrated that the fluctuations are intrinsically intermittent through a large excess kurtosis moment in the limit of weak pulse overlap. These results allow for estimation of the basic properties of fluctuations from measurement data and describe the diversity of frequency spectra reported from measurements in magnetized plasmas.

Scaling properties of signals as origin of 1/f noise

.There are several mathematical models yielding 1/f noise. For example, a 1/f spectrum can be obtained from a stochastic sequence of pulses with a power-law distribution of pulse durations or from nonlinear stochastic differential equations. We show that a couple of seemingly different models exhibiting a 1/f spectrum are due to similar scaling properties of the signals. In addition, we demonstrate a connection between signals with the power-law behavior of the power spectral density generated by the nonlinear stochastic differential equations and modeled by a sequence of random different pulses. An approximation of solutions of the nonlinear stochastic differential equations by the sequence of pulses correctly reproduces the power-law parts of the probability density function and of the power spectral density. This connection provides further insights into the origin of 1/f noise.

Temporal properties of the terrestrial gamma-ray flashes from the Gamma-Ray Burst Monitor on the Fermi Observatory

[1] The Gamma-Ray Burst Monitor (GBM) on the Fermi Gamma-Ray Space Telescope (Fermi) detected 50 terrestrial gamma-ray flashes (TGFs) during its first 20 months of operation. The high efficiency and large area of the GBM detectors, combined with their fine timing capabilities and relatively high throughput, allow unprecedented studies of the temporal properties of TGFs. The TGF pulses are observed to have durations as brief as ∼0.05 ms, shorter than previously measured. There is a relatively narrow distribution of pulse durations; the majority of pulses have total durations between 0.10 and 0.40 ms. In some TGF events, risetimes as short as ∼0.01 ms and falltimes as short as ∼0.03 ms are observed. Three of the 50 TGFs presented here have well-separated, double peaks. Perhaps as many as 10 other TGFs show evidence, to varying degrees, of overlapping peaks. Weak emission is seen at the leading or trailing edges of some events. Five of the 50 TGFs are considerably longer than usual; these are believed to be caused by incident electrons transported from a TGF at the geomagnetic conjugate point. TGF temporal properties can be used to discriminate between models of the origin of TGFs and also provide some basic physical properties of the TGF process.

Real-time measurement of noise statistics

There has been much interest in the statistics of electromagnetic noise such as amplitude probability distribution (APD), average crossing rate (ACR), pulse duration distribution (PDD), and pulse spacing distribution (PSD). Traditionally, noise statistics have been measured using a digitizer and personal computer. In such measurements, the total number of samples for calculating these statistics is limited by the amount of RAM in the digitizer. To remove this limitation, we have developed new statistics measuring equipment that digitizes the detected noise at a sampling rate of 20 MHz and classifies the sampled data into 256 levels with an accuracy of 30 bits. The frequency distribution of the classified data is calculated in histogram measuring circuits. Therefore, the frequency distribution is measured in real time based on a total of up to 10/sup 9/ samples. This paper describes the statistical measurement method and reports the statistics of noise leaked by a microwave oven in the 2.4-GHz band measured by the developed equipment. It was confirmed that the noise statistics with an occurrence probability of less than 10/sup -9/ can be measured.

Measurements and models of radio frequency impulsive noise for indoor wireless communications

The authors present the results of average and impulsive noise measurements inside several office buildings and retail stores. The noise measurement system operated at 918 MHz, 2.44 GHz, and 4 GHz with a nominal 40-MHz, 3-dB RF bandwidth. Omnidirectional and directional antennas were used to investigate the characteristics and sources of RF noise in indoor channels. Statistical analyses of the measurements are presented in the form of peak amplitude probability distributions, pulse duration distributions, and interarrival time distributions. Simple first-order mathematical models for these statistical characterizations are also presented. These analyses indicate that photocopiers, printers (both line printers and cash register receipt printers), elevators, and microwave ovens are significant sources of impulse noise in office and retail environments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Statistical characterization of v.h.f. man-made radio noise

Recordings of the detected envelope of v.h.f. man-made noise measured at various urban and suburban locations have been analysed to produce amplitude and time statistics. These are presented as graphs of amplitude probability distribution, average level crossing rate, pulse duration distribution and pulse interval distribution. Corresponding graphs at different locations have the same general form but the detailed shape varies with the density and pattern of traffic flow. There is evidence that occasional noise bursts exist with pulses too closely spaced in time to be adequately resolved by a narrow-band receiver.

Time and Amplitude Statistics for Electromagnetic Noise in Mines

The time and amplitude statistics illustrated are important and useful in describing the time-dependent, measured electromagnetic (EM) noise in mines. They are 1) Allan variance analyses (AVA), 2) interpulse spacing distributions (ISD), 3) pulse duration distributions (PDD), 4) average crossing rates (ACR), and 5) amplitude probability distributions (APD). These statistics are illustrated using a rather large store of raw analog data measured in operatioal mines through computer software techniques. The curves generated for the figures characterize the noise environment in the mines from which the corresponding data were taken, and should aid in the design of reliable communication systems for such mines.