The parity-check matrix of a linear code is used to define a bipartite code constraint (Tanner) graph in which bit nodes are connected to parity check nodes. The connectivity properties of this graph are analyzed using both local connectivity and the eigenvalues of the associated adjacency matrix. A simple lower bound on minimum distance of the code is expressed in terms of the two largest eige...

The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several diff...

A general parametrization for all three-dimensional crystal lattices is presented in this paper which guarantees that the three primitive vectors constructed by the parametrization are the three shortest possible, linearly independent lattice vectors existing in the whole lattice. The parameter space of this so-called minimum distance parametrization (MDP) can easily be confined to contain only...

This paper addresses the problem of designing nite impulse response lters which optimally approximate desired frequency responses in the sense that they minimize a perceptual audio spectral measure. This measure is based on a simpli ed auditory model similar to those used in the area of perceptual audio quality measurement. It is shown that this problem can be cast as a logarithmic Chebychev ap...

In this paper, we present a method for evaluating the minimum free Chernov distance of trellis-codes for a discrete memoryless channels(DMC). In order to design an e cient trellis-code for the DMC, we need to evaluate the minimum free Chernov distance of the target code. However, the lack of the additive property of the Chernov distance prevents a conventional branch-and-bound search for evalua...

The purpose of this paper is to introduce a new estimation method for estimating the Archimedean copula dependence parameter in the non-parametric setting. The estimation of the dependence parameter has been selected as the value that minimizes the Cramér-von-Mises distance which measures the distance between Empirical Bernstein Kendall distribution function and true Kendall distribution functi...