An overview of Sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, provide very good numerical approximations to the associated optimal state estimation problems. However, in many scenarios, the state-space model of interest also depends on unknown static parameters that need to be estimated from the data. In this context, standard SMC methods fail and it is necessary to rely on more sophisticated algorithms. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed to perform static parameter estimation in general state-space models. We discuss the advantages and limitations of these methods. © 2009 IFAC.

Multiple pitch estimation using non-homogeneous poisson processes

Novel statistical models are proposed and developed in this paper for automated multiple-pitch estimation problems. Point estimates of the parameters of partial frequencies of a musical note are modeled as realizations from a non-homogeneous Poisson process defined on the frequency axis. When several notes are combined, the processes for the individual notes combine to give a new Poisson process whose likelihood is easy to compute. This model avoids the data-association step of linking the harmonics of each note with the corresponding partials and is ideal for efficient Bayesian inference of unknown multiple fundamental frequencies in a signal. © 2011 IEEE.

The effects of a second tunnel on the propagation of ground-borne vibration from an underground railway

Accurate predictions of ground-borne vibration levels in the vicinity of an underground railway are greatly sought in modern urban centers. Yet the complexity involved in simulating the underground environment means that it is necessary to make simplifying assumptions about this environment. One such commonly-made assumption is to model the railway as a single tunnel, despite many underground railway lines consisting of twin-bored tunnels. A unique model for two tunnels embedded in a homogeneous, elastic full space is developed. The vibration response of this two-tunnel system is calculated using the superposition of two displacement fields: one resulting from the forces acting on the invert of a single tunnel, and the other resulting from the interaction between the tunnels. By partitioning of the stresses into symmetric and anti-symmetric mode number components using Fourier decomposition, these two displacement fields can by calculated with minimal computational requirements. The significance of the interactions between twin-tunnels is quantified by calculating the insertion gains that result from the existence of a second tunnel. The insertion-gain results are shown to be localized and highly dependent on frequency, tunnel orientation and tunnel thickness. At some locations, the magnitude of these insertion gains is greater than 20dB. This demonstrates that a high degree of inaccuracy exists in any surface vibration-prediction model that includes only one of the two tunnels. © 2012 Springer.