Delves into deriving the Kalman-Hauad-Morning relation in stationary turbulence, emphasizing homogeneity and isotropy assumptions, and culminates in the common Howard-Mohnen relation.
Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.
Explores the restoration of symmetries in fluid dynamics equations, particularly the Navier-Stokes equations in periodic domains, highlighting the significance of symmetry in understanding fluid motion.
