Explores the dynamics of a simple pendulum and the intriguing Lorenz equations, highlighting sensitivity to initial conditions and the transition to chaos.
Covers the modeling of fluid instabilities with linear perturbation theory and explores the origin of unpredictability in turbulence through the Navier-Stokes equations.
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.
