Shot-noise spectroscopy of energy resolved ballistic currents

We investigate the shot noise of nonequilibrium carriers injected into a ballistic conductor and interacting via long-range Coulomb forces. Coulomb interactions are shown to act as an energy analyzer of the profile of injected electrons by means of the fluctuations of the potential barrier at the emitter contact. We show that the details in the energy profile can be extracted from shot-noise measurements in the Coulomb interaction regime, but cannot be obtained from time-averaged quantities or shot-noise measurements in the absence of interactions.

Effect of long-range Coulomb interaction on shot-noise suppression in ballistic transport

We present a microscopic analysis of shot-noise suppression due to long-range Coulomb interaction in semiconductor devices under ballistic transport conditions. An ensemble Monte Carlo simulator self-consistently coupled with a Poisson solver is used for the calculations. A wide range of injection-rate densities leading to different degrees of suppression is investigated. A sharp tendency of noise suppression at increasing injection densities is found to scale with a dimensionless Debye length related to the importance of space-charge effects in the structure.

Characterizations of Life Distributions Using Conditional Expectations of Doubly (Interval) Truncated Random Variables

In this article, we study reliability measures such as geometric vitality function and conditional Shannon’s measures of uncertainty proposed by Ebrahimi (1996) and Sankaran and Gupta (1999), respectively, for the doubly (interval) truncated random variables. In survival analysis and reliability engineering, these measures play a significant role in studying the various characteristics of a system/component when it fails between two time points. The interrelationships among these uncertainty measures for various distributions are derived and proved characterization theorems arising out of them

Identification of models using failure rate and mean residual life of doubly truncated random variables

In this paper, we study the relationship between the failure rate and the mean residual life of doubly truncated random variables. Accordingly, we develop characterizations for exponential, Pareto 11 and beta distributions. Further, we generalize the identities for fire Pearson and the exponential family of distributions given respectively in Nair and Sankaran (1991) and Consul (1995). Applications of these measures in file context of lengthbiased models are also explored

Microstructure and random magnetic anisotropy in Fe–Ni based nanocrystalline thin films

Nanocrystalline Fe–Ni thin films were prepared by partial crystallization of vapour deposited amorphous precursors. The microstructure was controlled by annealing the films at different temperatures. X-ray diffraction, transmission electron microscopy and energy dispersive x-ray spectroscopy investigations showed that the nanocrystalline phase was that of Fe–Ni. Grain growth was observed with an increase in the annealing temperature. X-ray photoelectron spectroscopy observations showed the presence of a native oxide layer on the surface of the films. Scanning tunnelling microscopy investigations support the biphasic nature of the nanocrystalline microstructure that consists of a crystalline phase along with an amorphous phase. Magnetic studies using a vibrating sample magnetometer show that coercivity has a strong dependence on grain size. This is attributed to the random magnetic anisotropy characteristic of the system. The observed coercivity dependence on the grain size is explained using a modified random anisotropy model

ECG Noise Removal using GA tuned Sign-Data Least Mean Square Algorithm

Adaptive filter is a primary method to filter Electrocardiogram (ECG), because it does not need the signal statistical characteristics. In this paper, an adaptive filtering technique for denoising the ECG based on Genetic Algorithm (GA) tuned Sign-Data Least Mean Square (SD-LMS) algorithm is proposed. This technique minimizes the mean-squared error between the primary input, which is a noisy ECG, and a reference input which can be either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Noise is used as the reference signal in this work. The algorithm was applied to the records from the MIT -BIH Arrhythmia database for removing the baseline wander and 60Hz power line interference. The proposed algorithm gave an average signal to noise ratio improvement of 10.75 dB for baseline wander and 24.26 dB for power line interference which is better than the previous reported works

Implementation of a Neural Network Classifier for Noise Sources in the Ocean

The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral analysis. However, bispectral analysis, which is a higher order estimation technique, can reveal the presence of such phase couplings and provide a measure to quantify such couplings. A feed forward neural network has been trained and validated with higher order spectral features

Testing Isotropy and a related Random Walk problem

One comes across directions as the observations in a number of situations. The first inferential question that one should answer when dealing with such data is, “Are they isotropic or uniformly distributed?” The answer to this question goes back in history which we shall retrace a bit and provide an exact and approximate solution to this so-called “Pearson’s Random Walk” problem.

Queues with inter- ruption in Random/ Markovian Environment

In many situations probability models are more realistic than deterministic models. Several phenomena occurring in physics are studied as random phenomena changing with time and space. Stochastic processes originated from the needs of physicists.Let X(t) be a random variable where t is a parameter assuming values from the set T. Then the collection of random variables {X(t), t ∈ T} is called a stochastic process. We denote the state of the process at time t by X(t) and the collection of all possible values X(t) can assume, is called state space

Highly Sensitive Sensor Based On Intracavity Laser Absorption Spectroscopy By Means of Relative Intensity Noise

This thesis concerns with the main aspects of medical trace molecules detection by means of intracavity laser absorption spectroscopy (ICLAS), namely with the equirements for highly sensitive, highly selective, low price, and compact size sensor. A novel two modes semiconductor laser sensor is demonstrated. Its operation principle is based on the competition between these two modes. The sensor sensitivity is improved when the sample is placed inside the two modes laser cavity, and the competition between the two modes exists. The effects of the mode competition in ICLAS are discussed theoretically and experimentally. The sensor selectivity is enhanced using external cavity diode laser (ECDL) configuration, where the tuning range only depends on the external cavity configuration. In order to considerably reduce the sensor cost, relative intensity noise (RIN) is chosen for monitoring the intensity ratio of the two modes. RIN is found to be an excellent indicator for the two modes intensity ratio variations which strongly supports the sensor methodology. On the other hand, it has been found that, wavelength tuning has no effect on the RIN spectrum which is very beneficial for the proposed detection principle. In order to use the sensor for medical applications, the absorption line of an anesthetic sample, propofol, is measured. Propofol has been dissolved in various solvents. RIN has been chosen to monitor the sensor response. From the measured spectra, the sensor sensitivity enhancement factor is found to be of the order of 10^(3) times of the conventional laser spectroscopy.

Noise Reduction Using Low Weight and Constant Weight Coding Techniques

Signalling off-chip requires significant current. As a result, a chip's power-supply current changes drastically during certain output-bus transitions. These current fluctuations cause a voltage drop between the chip and circuit board due to the parasitic inductance of the power-supply package leads. Digital designers often go to great lengths to reduce this "transmitted" noise. Cray, for instance, carefully balances output signals using a technique called differential signalling to guarantee a chip has constant output current. Transmitted-noise reduction costs Cray a factor of two in output pins and wires. Coding achieves similar results at smaller costs.