System identification using evolutionary Markov chain Monte Carlo
نویسندگان
چکیده
منابع مشابه
System identification using evolutionary Markov chain Monte Carlo
System identi®cation involves determination of the functional structure of a target system that underlies the observed data. In this paper, we present a probabilistic evolutionary method that optimizes system architectures for the iden-ti®cation of unknown target systems. The method is distinguished from existing evolutionary algorithms (EAs) in that the individuals are generated from a probabi...
متن کاملEvolutionary Markov Chain Monte Carlo
Markov chain Monte Carlo (MCMC) is a popular class of algorithms to sample from a complex distribution. A key issue in the design of MCMC algorithms is to improve the proposal mechanism and the mixing behaviour. This has led some authors to propose the use of a population of MCMC chains, while others go even further by integrating techniques from evolutionary computation (EC) into the MCMC fram...
متن کاملAdaptive System Identification using Markov Chain Monte Carlo
One of the major problems in adaptive filtering is the problem of system identification. It has been studied extensively due to its immense practical importance in a variety of fields. The underlying goal is to identify the impulse response of an unknown system. This is accomplished by placing a known system in parallel and feeding both systems with the same input. Due to initial disparity in t...
متن کاملBayesian system identification via Markov chain Monte Carlo techniques
The work here explores new numerical methods for supporting a Bayesian approach to parameter estimation of dynamic systems. This is primarily motivated by the goal of providing accurate quantification of estimation error that is valid for arbitrary, and hence even very short length data records. The main innovation is the employment of the Metropolis–Hastings algorithm to construct an ergodic M...
متن کاملA Markov-Chain-Monte-Carlo-Based Method for System Identification
This paper describes a novel methodology for the identification of mechanical systems and structures from vibration response measurements. It combines prior information, observational data and predictive finite element models to produce configurations and system parameter values that are most consistent with the available data and model. Bayesian inference and a Metropolis simulation algorithm ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Systems Architecture
سال: 2001
ISSN: 1383-7621
DOI: 10.1016/s1383-7621(01)00017-0