Dynamical behaviour of low autocorrelation models

Dynamical Behaviour of Low Autocorrelation Models

We have investigated the nature of the dynamical behaviour in low autocorrelation binary sequences. These models do have a glass transition TG of a purely dynamical nature. Above the glass transition the dynamics is not fully ergodic and relaxation times diverge like a power law τ ∼ (T − TG) with γ close to 2. Approaching the glass transition the relaxation slows down in agreement with the firs...

Dynamical Behaviour of Low Autocorrelation Models

Extracting dynamical behaviour via Markov models

Ulam's method of discretising the dynamics of a smooth deterministic system to produce a nite state Markov chain approximation has been in use for over two decades. We review what can be done with the constructions, in the sense of how various dy-namical indicators and behaviour can be numerically extracted.

Zooplankton mortality and the dynamical behaviour of plankton population models.

We investigate the dynamical behaviour of a simple plankton population model, which explicitly simulates the concentrations of nutrient, phytoplankton and zooplankton in the oceanic mixed layer. The model consists of three coupled ordinary differential equations. We use analytical and numerical techniques, focusing on the existence and nature of steady states and unforced oscillations (limit cy...

Considering Autocorrelation in Predictive Models

Most machine learning, data mining and statistical methods rely on the assumption that the analyzed data points are independent and identically distributed (i.i.d.). More specifically, the individual examples included in the training data are assumed to be drawn independently from each other from the same probability distribution. However, cases where this assumption is violated can be easily f...