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Author Rice, J. R. ♦ Pa, Bethlehem ♦ Beer, F. P.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Mechanic Department ♦ Lehigh University ♦ Probability Density ♦ Mi Random Process ♦ Random Loading ♦ Available Experimental Data ♦ Numerical Result ♦ Random Continuous Function ♦ Stationary Gaussian Process ♦ Continuous Random Process ♦ Independent Variable ♦ Differentiable Random Function ♦ Statistical Information ♦ Problem Consider ♦ Gaussian Distribution ♦ General Result ♦ Approximate Method ♦ Special Case
Abstract mis Random Process This paper is concerned with the statistics of the height of rise and fall for continuous random processes. In particular, approximate methods are given for determining the probability density of the increment in a random continuous function as the function passes from one extremum to the next. Application of the general result is made to the case of processes with a Gaussian distribution. Numerical results are given for four special cases of stationary Gaussian processes. Computed results are found to agreewell with available experimental data. The knowledge of such statistical information is of use in studies dealing with fatigue under random loadings. Statement of Problem CONSIDER a continuous and twice differentiable random function, x(t). The purpose of this work is to predict the probability density for the height of rise or fall of x{t) as this function passes from one extremum to the next. In what follows it will be convenient to view the independent variable t as the
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article