This paper investigates the correspondence matching of point-sets using spectral graph analysis. In particular, we are interested in the problem of how the modal analysis of point-sets can be rendered robust to contamination and drop-out. We make three contributions. First, we show how the modal structure of point-sets can be embedded within the framework of the EM algorithm. Second, we present...

In this paper, we describe the use of Riemannian geometry, and in particular the relationship between the Laplace-Beltrami operator and the graph Laplacian, for the purposes of embedding a graph onto a Riemannian manifold. Using the properties of Jacobi fields, we show how to compute an edge-weight matrix in which the elements reflect the sectional curvatures associated with the geodesic paths ...

This paper investigates the correspondence matching of point-sets using spectral graph analysis. In particular we are interested in the problem of how the modal analysis of point-sets can be rendered robust to contamination and drop-out. We make three contributions. First, we show how the modal structure of point-sets can be embedded within the framework of the EM algorithm. Second, we present ...

A multi-pattern encoding and decoding scheme is presented that extends the family of spectral associative memories (SAMs) to include gray-level, or analog patterns. SAMs are frequency-domain formulations of associative memory that combine the extrinsic redundancy of neural networks with the in-phase, quadrature, and complex modulation schemes of communications. Considerable coding gain occurs a...

Pattern recognition is a multidisciplinary area that received more scientific attraction during this period of rapid technological innovation. Today, many real issues and scenarios require pattern to aid in the faster resolution complicated problems, particularly those cannot be solved using traditional human heuristics. One common problem dealing with multidimensional data, which prominent stu...