Profile Likelihood Ratio Analysis Techniques for Rare Event Signals

Rare Event Provoking Simulation Techniques

Importance sampling is the rare event provoking technique that is most frequently used for speed-up simulation of dependability and traffic models. Due to its sensitivity to the parameter settings, it is not yet ready for practical use. There exists a number of approaches for finding optimal, or at least good, parameters. The applicability of these and necessary extensions are discussed with re...

Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

Orthogonal frequency division multiplexing (OFDM) has been adopted as a standard for many modern wireless applications requiring high data rate due to bandwidth efficiency, resistance to frequency selective fading and simple digital realization using IFFT/FFT operations. However, physical implementation of the OFDM system suffers from several difficulties. One of the major limitations of OFDM i...

Likelihood Ratio Tests for

Rare-event Probability Estimation via Empirical Likelihood Maximization

We explore past and recent developments in rare-event probability estimation with a particular focus on a novel Monte Carlo technique – Empirical Likelihood Maximization (ELM). This is a versatile method that involves sampling from a sequence of densities using MCMC and maximizing an empirical likelihood. The quantity of interest, the probability of a given rare-event, is estimated by solving a...

Blind Source Separation Techniques for Decomposing Event-Related Brain Signals

Recently blind source separation (BSS) methods have been highly successful when applied to biomedical data. This paper reviews the concept of BSS and demonstrates its usefulness in the context of event-related MEG measurements. In a first experiment we apply BSS to artifact identification of raw MEG data and discuss how the quality of the resulting independent component projections can be evalu...