A new algorithm based on least-squares method for harmonic and interharmonic analysis is proposed. The approach employs least-squares method and is based on a linear prediction relation for multiple sinusoidal signals. It is shown that the method allows for accurate harmonic and interharmonic estimation with high frequency resolution. The approach is compared with that of DFT method and prony m...

A continuous extension of the objective function to a projective space guarantees that for each data set there exists at least one hyperplane or hypersphere minimizing the average squared distance to the data. For data sufficiently close to a hypersphere, as the collinearity of the data increases, so does the sensitivity of the fitted hypersphere to perturbations of the data.

The estimation of shaping filters with the `1-norm as opposed to the `2-norm leads to a proper attenuation of multiples when significant amplitude discrepancies exist between multiples and primaries. The actual method implemented is the fairly standard iteratively re-weighted least-squares method which is an excellent approximation to `1. Synthetic and field data results illustrate the advantag...

This paper presents a new algorithm that is capable of extracting circles from complicated and heavily corrupted images. The algorithm uses a least-squares fitting algorithm for arc segments. The arcs are segmented by using the short straight lines which are extracted by a fast line extraction algorithm. The arc segments are used to yield accurate circle parameters. Tests performed on synthetic...

Orbital solutions for binary or multiple stellar systems that combine astrometry (e.g., position angles and angular separations) with spectroscopy (radial velocities) have important advantages over astrometric-only or spectroscopic-only solutions. In many cases they allow the determination of the absolute masses of the components, as well as the distance. Yet, these kinds of combined solutions ...

Iterative processes for the inversion of structured matrices can be further improved by using a technique for compression and refinement via the least-squares computation. We review such processes and elaborate upon incorporation of this technique into the known frameworks.

Previous studies on fuzzy linear regression analysis have a common characteristic of increasing spreads for the estimated fuzzy responses as the independent variable increases its magnitude, which is not suitable for general cases. This paper proposes a two-stage approach to construct the fuzzy linear regression model. In the 2rst stage, the fuzzy observations are defuzzi2ed so that the traditi...

We present a method to determine 3D motion and structure of multiple objects from two perspective views, using adaptive Hough transform. In our method, segmentation is determined based on a 3D rigidity constraint. Instead of searching candidate solutions over the entire five-dimensional translation and rotation parameter space, we only examine the two-dimensional translation space. We divide th...

ÐA local image transform based on cumulative similarity measures is defined and is shown to enable efficient correspondence and tracking near occluding boundaries. Unlike traditional methods, this transform allows correspondences to be found when the only contrast present is the occluding boundary itself and when the sign of contrast along the boundary is possibly reversed. The transform is bas...

We introduce the reader to the mathematics behind projection of n-dimensional vectors into a basis on n-dimensional space, where n can be anything upto and including infinity. We show how ideally one wants to project into the duals of a basis if this basis is not orthonormal, and provide the mathematics to formulate this operation in matrix form. The second part of the article discusses spheric...