Multidimentional and Multi-Parameter Fortran-Based Curve Fitting Tools

Kernel Based Algebraic Curve Fitting

An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of vectors labelled as interior or exterior to the curve. The problem of fitting a linear curve in this way is shown to lend itself to a support vector representation, allowing non-linear curves and high dimensional surface...

The best parameter subset using the Chebychev curve fitting criterion

Signal detection Using Rational Function Curve Fitting

In this manuscript, we proposed a new scheme in communication signal detection which is respect to the curve shape of received signal and based on the extraction of curve fitting (CF) features. This feature extraction technique is proposed for signal data classification in receiver. The proposed scheme is based on curve fitting and approximation of rational fraction coefficients. For each symbo...

Curve Fitting and Polymers

1 Curve Fitting and Polymers The availability of data from well-characterized samples such as those offered by Beamson and Briggs [1] owe much to the popularity of XPS as a tool for understanding the chemistry of polymers. A typical C 1s envelope [2] (Figure 1) includes structure that offers chemical information about a sample, but without some initial starting point it is difficult to construc...

Multi-class Markovian arrival processes and their parameter fitting

Markovian arrival processes are a powerful class of stochastic processes to represent stochastic workloads that include autocorrelation in performance or dependability modeling. However, fitting the parameters of a Markovian arrival process to given measurement data is non-trivial and most known methods focus on a single class case, where all events are of the same type and only the sequence of...