2017/03/26 by Khem Raj Ghusinga, Mohammad Soltani, Ghusinga, Khem Raj +7
Biochemistry, Genetics and Molecular Biology · Chemistry · Physics and Astronomy · #FOS: Mathematics #Gene Regulatory Network Analysis #Mass Spectrometry Techniques and Applications #Optimization and Control (math.OC) #Probability (math.PR) #Quantum chaos and dynamical systems #Spectroscopy and Quantum Chemical Studies
paper · pdf · doi:10.48550/arxiv.1703.08841
openalex publication_date 2017/03/26 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Stochastic dynamical systems often contain nonlinearities which make it hard\nto compute probability density functions or statistical moments of these\nsystems. For the moment computations, nonlinearities in the dynamics lead to\nunclosed moment dynamics; in particular, the time evolution of a moment of a\nspecific order may depend both on moments of order higher than it and on some\nnonlinear function of other moments. The moment closure techniques are used to\nfind an approximate, close system of equations the moment dynamics. In this\nwork, we extend a moment closure technique based on derivative matching that\nwas originally proposed for polynomial stochastic systems with discrete states\nto continuous state stochastic systems to continuous state stochastic\ndifferential equations, with both polynomial and trigonometric nonlinearities.\nWe validate the technique using two examples of nonlinear stochastic systems.\n