Frequency domain identification of Wiener models

This paper proposes a frequency domain algorithm for Wiener model identifications based on exploring the fundamental frequency and harmonics generated by the unknown nonlinearity. The convergence of the algorithm is established in the presence of white noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.     

Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.     

An exploration of the problems of using function points mark II

Abstract. This paper examines critically the function point analysis mark II (FPA mark II) method of measuring the functionality of information systems. Although the focus of the paper is on FPA mark II as devised by Symons, both this and the Albrecht method, from which the FPA mark II was developed, are briefly discussed. The published attempts to validate FPA mark II are reviewed and then the problems encountered by the author in applying the approach are described. The final part of the paper is concerned with the fit between SSADM and FPA mark II.     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

SPECTRAL DENSITY ESTIMATION FROM NONLINEARLY OBSERVED DATA

Abstract. The estimation of the spectral density function of a stationary Gaussian process at the input of an instantaneous nonlinearity is considered when the nonlinearity is known and a finite set of observations of the output process is given. A class of spectral estimates is considered and their quadratic-mean consistency is established; precise asymptotic expressions for their bias and covariance are derived and their asymptotic normality is obtained.     

Approximate channel identification via δ‐signed correlation

A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ‘smoothly’ from a situation with small sum‐squared channel estimation error but hard‐to‐identify channel peaks, to one with a larger sum‐squared estimation error but easy‐to‐identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd.     

Empirical Evaluations of Usage-Based Reading and Fault Content Estimation for Software Inspections

This thesis describes six empirical investigations of two techniques applied to software inspections, namely reading techniques and fault content estimation techniques. The first part of the thesis presents a series of experiments of a novel reading technique called usage-based reading. The second part investigates fault content estimation applied to the software inspection process. The estimation methods used are capture-recapture and curve fitting.     

定容气田开发规划概算法

基于物质平衡方程、产能方程和递减方程的结合,提出了定容气田开发规划的概算法.该法可用于预测地层压力、井底流动压力、井口流动压力和稳产年限.实际应用表明,本文提供的方法是实用有效的.     

Non-steady-state model for kinetics of free radical polymerization, 4. Direct thermal initiation

This paper deals with the non-steady-state kinetics of direct thermal initiated polymerization. The initiation is assumed to be a bimolecular reaction of the monomer. The relationship between the radical concentration and the monomer conversion is rigorously derived. In further treatment a few very close approximations are introduced based on the fact that the number of monomer molecules reacting in the initiation step is much less than that consumed in the propagation step for a process producing high polymer, and the value of the rate constant for propagation or chain transfer is much lower than that for chain termination. Expressions for various molecular parameters, such as molecular weight distribution, number-average and weight-average degrees of polymerization, and dispersity, are given. Several numerical examples are provided.