We present an iterative algorithm, called the symmetric tensor eigen-rank-one iterative decomposition (STEROID), for decomposing a symmetric tensor into a real linear combination of symmetric rank-1 unit-norm outer factors using only eigendecompositions and least-squares fitting. Originally designed for quartic (4th-order) symmetric tensors, STEROID is shown to be applicable to any order throug...

The progressive and iterative approximation (PIA) method is an efficient and intuitive method for data fitting. However, in the classical PIA method, the number of the control points is equal to that of the data points. It is not feasible when the number of data points is very large. In this paper, we develop a new progressive and iterative approximation for least square fitting (LSPIA). LSPIA ...

While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random e...

A piecewise algebraic curve is defined as the zero contour of a bivariate spline. In this paper, we present a new method for fitting C1 piecewise algebraic curves of degree 2 over type-2 triangulation to the given scattered data. By simultaneously approximating points, associated normals and tangents, and points constraints, the energy term is also considered in the method. Moreover, some examp...