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.

Sequential analysis for testing quality standard of fish ham and sausage

Fish sausages are finely ground fish flesh, either of a single species or mixed, homogenised with starch, sugar, fat, spices and preservatives, generally filled in cylindrical synthetic or natural casings and pasteurised. Similar products containing small pieces of quality fish and lard are termed "fish ham". They are highly relished products in Japan, annual consumption exceeding 2 lakh tones. Preliminary studies have shown that they can catch a lucrative market in our country. However, being a pasteurised product which is often consumed as such without any further cooking, strict quality control measures have to be enforced so as to avoid food poisoning hazards. Besides physical characteristics like absence of damages, pin-holes, curliness and air pockets as well as jelly strength, texture and flavour, chemical characteristics like pH and acid values, moisture, carbohydrate and fat contents and volatile bases have to be assessed. A very important test that has to be carried out along with the above, before passing a lot for free distribution is the bacteriological examination to avoid the presence of pathogenic organisms.

A paradigm for virus-host coevolution: Sequential counter-adaptations between endogenous and exogenous retroviruses

Endogenous retroviruses ( ERVs) are remnants of ancient retroviral infections of the host germline transmitted vertically from generation to generation. It is hypothesized that some ERVs are used by the host as restriction factors to block the infection o

Adaptive sequential Monte Carlo approach for real-time applications

This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.