Add to ORKGReal and complex exponential data fitting is an important activity in many different areas of science and engineering, ranging from Nuclear Magnetic Resonance Spectroscopy and Lattice Quantum Chromodynamics to Electrical and Chemical Engineering, Vision and Robotics. The most commonly used norm in the approximation by linear combinations of exponentials is the l2 norm (sum of squares of residuals), in which case one obtains a nonlinear separable least squares problem. A number of different methods have been proposed through the years to solve these types of problems and new applications appea
This paper focuses on why the regular least–squares fitting technique is unstable when used to fit e...
Exponential fitted algorithms for initial value and boundary value methods and for the calculation o...
summary:A numerical method of fitting a multiparameter function, non-linear in the parameters which ...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/77...
In this paper, we estimate the parameters of the exponential distribution by least trimmed squares (...
A finite sum of exponential functions may be expressed by a linear combination of powers of the inde...
summary:One has to find a real function $y(x_1,x_2,\dots ,x_n)$ of variables $x_i$, $i=1,2,\dots,x_n...
This thesis examines how to find the best fit to a series of data points when curve fitting using po...
Signal waveforms are very fast dampening oscillatory time series composed of exponential functions. ...
This thesis explores how to best choose data when curve fitting using power exponential functions. T...
Curve fitting discrete data (x, y) with a smooth function is a complex problem when faced with sharp...
The question in the title is answered empirically by solving instances of three classical problems: ...
This paper focuses on why the regular least–squares fitting technique is unstable when used to fit e...
Abstract We consider a range of robust data fitting problems which have attracted interest so far in...
The standard monograph in this area is the book Exponential fitting by Ixaru and Vanden Berghe (Kluw...
This paper focuses on why the regular least–squares fitting technique is unstable when used to fit e...
Exponential fitted algorithms for initial value and boundary value methods and for the calculation o...
summary:A numerical method of fitting a multiparameter function, non-linear in the parameters which ...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/77...
In this paper, we estimate the parameters of the exponential distribution by least trimmed squares (...
A finite sum of exponential functions may be expressed by a linear combination of powers of the inde...
summary:One has to find a real function $y(x_1,x_2,\dots ,x_n)$ of variables $x_i$, $i=1,2,\dots,x_n...
This thesis examines how to find the best fit to a series of data points when curve fitting using po...
Signal waveforms are very fast dampening oscillatory time series composed of exponential functions. ...
This thesis explores how to best choose data when curve fitting using power exponential functions. T...
Curve fitting discrete data (x, y) with a smooth function is a complex problem when faced with sharp...
The question in the title is answered empirically by solving instances of three classical problems: ...
This paper focuses on why the regular least–squares fitting technique is unstable when used to fit e...
Abstract We consider a range of robust data fitting problems which have attracted interest so far in...
The standard monograph in this area is the book Exponential fitting by Ixaru and Vanden Berghe (Kluw...
This paper focuses on why the regular least–squares fitting technique is unstable when used to fit e...
Exponential fitted algorithms for initial value and boundary value methods and for the calculation o...
summary:A numerical method of fitting a multiparameter function, non-linear in the parameters which ...