Scientific Research Publishing

Papoulis (1965) Probability, Random Variables, and Stochastic Processes. McGraw Hill, Inc.

ABSTRACT: Repeated convolution and truncation of a truncated fat-tailed distribution, instead of Monte Carlo simulation, for pricing a discrete, simple barrier option is presented. The parameters for ...
Microwaves & RF

Estimating the Crest Factor (Peak-to-RMS Ratio) for a Sum of Sinusoidal Signals

Signals composed of a sum of sinusoids are often used when testing components and systems. The peak-to-RMS value of the sum stresses the dynamic range of the component or system, thus correcting a ...
IEEE

A Novel Stochastic Model for IRS-Assisted Communication Systems Based on the Sum-Product of Nakagami-m Random Variables

Abstract: This paper presents exact formulas for the probability distribution function (PDF) and moment generating function (MGF) of the sum-product of statistically independent but not necessarily ...
Frontiers

Innovative stochastic finite difference approach for modelling unsteady non-Newtonian mixed convective fluid flow with variable thermal conductivity and mass diffusivity

A novel stochastic numerical scheme is introduced to solve stochastic differential equations. The development of the scheme is based on two different parts. One part finds the solution for the ...
IEEE

Achieving an Accurate Random Process Model for PV Power Using Cheap Data: Leveraging the SDE and Public Weather Reports

Abstract: Stochastic differential equation (SDE)-based random process models of renewable energy sources (RESs) jointly capture evolving probability distribution and temporal correlation in continuous ...
Electronic Design

Phase-Noise Modeling, Simulation, and Propagation in Phase-Locked Loops (Part 1)

Some brief theory and typical measurements of phase noise. Standard analysis of PLL phase noise used by most CAD applications. How to produce the lowest phase noise at a PLL output. A standard design ...
Frontiers

Adversarial robustness in deep neural networks based on variable attributes of the stochastic ensemble model

1 Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategy Support Force Information Engineering University, Zhengzhou, Henan, China 2 PLA Strategy Support Force Information ...
Interesting Engineering

Scientists demonstrate control over quantum randomness using laser bias

“We can now control quantum randomness in a vacuum,” claim scientists. It’s hard to think of a vacuum, as it’s a place devoid of matter or light. But in the quantum world, this isn’t true. Tiny ...
Scientific Research Publishing

Papoulis, A. and Pillai, U. (2002) Probability, Random Variables and Stochastic Processes. 4th Edition, McGraw Hill, Boston.

ABSTRACT: The original Bell inequality was obtained in a statistical derivation assuming three mutually cross-correlated random variables (four in the later version). Given that observations destroy ...