In this paper we investigate the use of description length principles to select an appropriate number of basis functions for functional data. We provide a flexible definition of the dimension of a random function that is constructed directly from the Karhunen-Loève expansion of the observed...

In this paper we examine the use of neural networks as a tool for predicting the success of basketball teams in the National Basketball Association (NBA). Statistics for 620 NBA games were collected and used to train a variety of neural networks such as feed-forward, radial basis, probabilistic...

Stochastic resonance (SR) induced by the signal modulation is investigated, by introducing the signal-modulated gain into a single-mode laser system. Using the linear approximation method, we detailedly calculate the signal-to-noise ratio (SNR) of a gain-noise model of the single-mode laser,...

Stochastic resonance (SR) in an over-damped linear system subjected to an excitation of bias signal modulated noise with multiplicative and additive noises is investigated. We obtain the exact expressions of the first two moments and the signal-to-noise ratio (SNR) of the output by using...

The stochastic resonance in a bias monostable system subject to frequency mixing force and multiplicative and additive noise is investigated. Based on the adiabatic elimination theory, the analytic expressions of the signal-to-noise ratio (SNR) for the fundamental and higher harmonics are...

We explore the collective response of an uncoupled parallel array of saturating dynamical subsystems to a noisy periodic or random signal. Numerical simulation results show that a parallel array of nonlinear saturating subsystems can enhance the signal transmission via tuning the internal noise...

The use of description length principles to select an appropriate number of basis functions for functional data is investigated. A flexible definition of the dimension of a random function that is constructed directly from the Karhunen–Loève expansion of the observed process or data...

The paper evaluates the quality of the German national accounting data (GDP and its useside components) as measured by the magnitude and dispersion of the forecast / revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...