Symbolic analytical modeling of normal processes in stochastic systems with complex fraction order Bessel nonlinearities

Methodological and algorithmical support for analytical modeling of normal (Gaussian) processes in continuous and discrete stochastic systems (StS) with complex fractional order Bessel nonlinearities (spherical, modified spherical, and Airy) is given. The developed StS support is based on the methods of normal approximation and statistical linearization. For complex fractional order, Bessel nonlinearities series and Hermite representations are used. Special attention is paid to symbolic algorithms and software based on modern computer algebra systems (CAS). A short survey of CAS StS application is given. The test example is devoted to noise immunity of Bessel fraction order oscillator in stochastic media.