Results 1  10
of
250
Perspectives on system identification
 In Plenary talk at the proceedings of the 17th IFAC World Congress, Seoul, South Korea
, 2008
"... System identification is the art and science of building mathematical models of dynamic systems from observed inputoutput data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous ne ..."
Abstract

Cited by 160 (3 self)
 Add to MetaCart
System identification is the art and science of building mathematical models of dynamic systems from observed inputoutput data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications. System identification is a very large topic, with different techniques that depend on the character of the models to be estimated: linear, nonlinear, hybrid, nonparametric etc. At the same time, the area can be characterized by a small number of leading principles, e.g. to look for sustainable descriptions by proper decisions in the triangle of model complexity, information contents in the data, and effective validation. The area has many facets and there are many approaches and methods. A tutorial or a survey in a few pages is not quite possible. Instead, this presentation aims at giving an overview of the “science ” side, i.e. basic principles and results and at pointing to open problem areas in the practical, “art”, side of how to approach and solve a real problem. 1.
Organizational market information processes: Cultural antecedents and new product outcomes
 JOURNAL OF MARKETING RESEARCH
, 1995
"... ..."
Estimation of Parameters and Eigenmodes of Multivariate Autoregressive Models
, 2001
"... Dynamical characteristics of a complex system can often be inferred from analyses of a stochastic time series model fitted to observations of the system. Oscillations in geophysical systems, for example, are sometimes characterized by principal oscillation patterns, eigenmodes of estimated autoregre ..."
Abstract

Cited by 100 (2 self)
 Add to MetaCart
Dynamical characteristics of a complex system can often be inferred from analyses of a stochastic time series model fitted to observations of the system. Oscillations in geophysical systems, for example, are sometimes characterized by principal oscillation patterns, eigenmodes of estimated autoregressive (AR) models of first order. This paper describes the estimation of eigenmodes of AR models of arbitrary order. AR processes of any order can be decomposed into eigenmodes with characteristic oscillation periods, damping times, and excitations. Estimated eigenmodes and confidence intervals for the eigenmodes and their oscillation periods and damping times can be computed from estimated model parameters. As a computationally efficient method of estimating the parameters of AR models from highdimensional data, a stepwise least squares algorithm is proposed. This algorithm computes model coefficients and evaluates criteria for the selection of the model order stepwise for AR models of successively decreasing order. Numerical simulations indicate that, with the least squares algorithm, the AR model coefficients and the eigenmodes derived from the coefficients are estimated reliably and that the approximate 95% confidence intervals for the coefficients and eigenmodes are rough approximations of the confidence intervals inferred from the simulations.
A Historical Application Profiler for Use by Parallel Schedulers
 In Job Scheduling Strategies for Parallel Processing
, 1997
"... Scheduling algorithms that use application and system knowledge have been shown to be more effective at scheduling parallel jobs on a multiprocessor than algorithms that do not. This paper focuses on obtaining such information for use by a scheduler in a network of workstations environment. The log ..."
Abstract

Cited by 82 (0 self)
 Add to MetaCart
(Show Context)
Scheduling algorithms that use application and system knowledge have been shown to be more effective at scheduling parallel jobs on a multiprocessor than algorithms that do not. This paper focuses on obtaining such information for use by a scheduler in a network of workstations environment. The log files from three parallel systems are examined to determine both how to categorize parallel jobs for storage in a job database and what job information would be useful to a scheduler. A Historical Profiler is proposed that stores information about programs and users, and manipulates this information to provide schedulers with execution time predictions. Several preemptive and nonpreemptive versions of the FCFS, EASY and Least Work First scheduling algorithms are compared to evaluate the utility of the profiler. It is found that both preemption and the use of application execution time predictions obtained from the Historical Profiler lead to improved performance.
Variable Selection for Regression Models
, 1998
"... A simple method for subset selection of independent variables in regression models is proposed. We expand the usual regression equation to an equation that incorporates all possible subsets of predictors by adding indicator variables as parameters. The vector of indicator variables dictates which pr ..."
Abstract

Cited by 75 (2 self)
 Add to MetaCart
A simple method for subset selection of independent variables in regression models is proposed. We expand the usual regression equation to an equation that incorporates all possible subsets of predictors by adding indicator variables as parameters. The vector of indicator variables dictates which predictors to include. Several choices of priors can be employed for the unknown regression coefficients and the unknown indicator parameters. The posterior distribution of the indicator vector is approximated by means of the Markov chain Monte Carlo algorithm. We select subsets with high posterior probabilities. In addition to linear models, we consider generalized linear models.
Molecular Modeling Of Proteins And Mathematical Prediction Of Protein Structure
 SIAM Review
, 1997
"... . This paper discusses the mathematical formulation of and solution attempts for the socalled protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possib ..."
Abstract

Cited by 59 (5 self)
 Add to MetaCart
(Show Context)
. This paper discusses the mathematical formulation of and solution attempts for the socalled protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible pathways to folding and unfolding, including the stability of the folded protein. From a mathematical point of view, there are several main sides to the static problem:  the selection of an appropriate potential energy function;  the parameter identification by fitting to experimental data; and  the global optimization of the potential. The dynamic problem entails, in addition, the solution of (because of multiple time scales very stiff) ordinary or stochastic differential equations (molecular dynamics simulation), or (in case of constrained molecular dynamics) of differentialalgebraic equations. A theme connecting the static and dynamic aspect is the determination and formation of...
Proactive Management of Software Aging
, 2001
"... this paper may be copied or distributed royalty free without further permission by computerbased and other informationservice systems. Permission to republish any other portion of this paper must be obtained from the Editor. ..."
Abstract

Cited by 57 (3 self)
 Add to MetaCart
this paper may be copied or distributed royalty free without further permission by computerbased and other informationservice systems. Permission to republish any other portion of this paper must be obtained from the Editor.
Uncertainty in surfacefire history: the case of ponderosa pine forests in the western United States
, 2001
"... Abstract: Present understanding of fire ecology in forests subject to surface fires is based on firescar evidence. We present theory and empirical results that suggest that firehistory data have uncertainties and biases when used to estimate the population mean fire interval (FI) or other paramet ..."
Abstract

Cited by 56 (1 self)
 Add to MetaCart
(Show Context)
Abstract: Present understanding of fire ecology in forests subject to surface fires is based on firescar evidence. We present theory and empirical results that suggest that firehistory data have uncertainties and biases when used to estimate the population mean fire interval (FI) or other parameters of the fire regime. First, the population mean FI is difficult to estimate precisely because of unrecorded fires and can only be shown to lie in a broad range. Second, the interval between tree origin and first fire scar estimates a real firefree interval that warrants inclusion in meanFI calculations. Finally, inadequate sampling and targeting of multiplescarred trees and high scar densities bias mean FIs toward shorter intervals. In ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) forests of the western United States, these uncertainties and biases suggest that reported mean FIs of 2–25 years significantly underestimate population mean FIs, which instead may be between 22 and 308 years. We suggest that uncertainty be explicitly stated in firehistory results by bracketing the range of possible population mean FIs. Research and improved methods may narrow the range, but there is no statistical or other method that can eliminate all uncertainty. Longer mean FIs in ponderosa pine forests suggest that (i) surface fire is still important, but less so in maintaining forest structure, and (ii) some dense patches of trees may have occurred in the preEuroAmerican landscape. Creation of lowdensity forest structure across all parts of ponderosa pine landscapes, particularly in valuable parks and reserves, is not supported by these results. Résumé: La compréhension actuelle de l’écologie du feu dans les forêts sujettes aux feux de surface repose sur la présence des cicatrices laissées par le feu. Nous présentons des résultats théoriques et empiriques qui montrent que les données sur l’historique des feux comportent des incertitudes et des biais lorsqu’elles sont utilisées pour estimer l’intervalle moyen entre les feux ou d’autres paramètres du régime des feux. Premièrement, il est difficile d’estimer avec précision
Combination of Machine Scores for Automatic Grading of Pronunciation Quality
, 1998
"... This work is part of an effort aimed at developing computerbased systems for language instruction; we address the task of grading the pronunciation quality of the speech of a student of a foreign language. The automatic grading system uses SRI's Decipher^TM continuous speech recognition syste ..."
Abstract

Cited by 37 (5 self)
 Add to MetaCart
This work is part of an effort aimed at developing computerbased systems for language instruction; we address the task of grading the pronunciation quality of the speech of a student of a foreign language. The automatic grading system uses SRI's Decipher^TM continuous speech recognition system to generate phonetic segmentations. Based on these segmentations and probabilistic models we produce different pronunciation scores for individual or groups of sentences that can be used as predictors of the pronunciation quality. Different types of these machine scores can be combined to obtain a better prediction of the overall pronunciation quality. In this paper we review some of the bestperforming machine scores, and discuss the application of several methods based on linear and nonlinear mapping and combination of individual machine scores to predict the pronunciation quality grade that a human expert would have given. We evaluate these methods in a database that consists of pronunciationqualitygraded speech from American students speaking French. With predictors based on spectral match and on durational characteristics, we find that the combination of scores improved the prediction of the human grades and that nonlinear mapping and combination methods performed better than linear ones. Characteristics of the different nonlinear methods studied are discussed.