Trajectory sensitivities complement time domain simulation in the analysis of large disturbance dynamic behaviour of power systems. They are formed by linearization around a nonlinear, and possibly non-smooth, trajectory. The influence of parameter variations on large disturbance behaviour can be estimated (to first order) from these sensitivities. Large (small) sensitivities indicate that a pa...

Residual echo arises in hands–free telephony equipment due to insufficient echo canceler convergence, but can be suppressed using a postfilter. The residual echo power spectral density is the most crucial control parameter for both frequency–domain acoustic echo cancellation and combined residual echo and noise postfiltering. In this contribution we present and compare residual echo power spect...

Module temperature is an important parameter of photovoltaic energy systems since their performance is affected by its variation. Several cooling controllers require a precise estimation of module temperature to reduce excessive heating and power losses. In this work, an adaptive neuro fuzzy inference system technique is developed for temperature estimation of photovoltaic systems. For the lear...

A function based nonlinear least squares estimation (FNLSE) method is proposed and investigated in parameter estimation of Jelinski–Moranda software reliability model. FNLSE extends the potential fitting functions of traditional least squares estimation (LSE), and takes the logarithm transformed nonlinear least squares estimation (LogLSE) as a special case. A novel power transformation function...

Signal processing algorithms and architectures can use dynamic reconfiguration to exploit variations in signal statistics with the objectives of improved performance and reduced power. Parameters provide a simple and formal way to characterize incremental changes to a computation and its computing mechanism. This paper develops a framework for dynamic parameterization and applies it to MPEG-4 m...

Inverse problems are typically solved under the assumption of known geometric system parameters describing the forward problem. Should such information be unavailable or inexact, the estimation of these parameters from only observed sensor data may be necessary prior to reconstruction of the desired signal. We demonstrate the feasibility of such estimation via maximum-likelihood methods for the...

1 Goal SPEM (S-system Parameter Estimation Method) package allows for the computation of parameters in the n-gene S-system from time series data. 2 Introduction Biological systems are composed of interacting components [1]. The process of the expression and the interactions of these components are nonlinear. S-systems have a power law formalism which is general enough to capture the base of the...

During the last years, a number of methodological papers on models with discrete parameter shifts have revived interest in the so-called regime switching models. Piecewise linear models are attractive when modelling a wide range of nonlinear system and determining simultaneously i) the data partition ii) the time instant of change iii) the parameter values of the different local models. This is...