A highly modular adaptive lattice algorithm for multichannel least squares filtering

In this paper a highly modular adaptive lattice algorithm for multichannel least squares FIR filtering and multivariable system identification is presented. Multichannel filters with different number of delay elements per input channel are allowed. The main features of the proposed multichannel adaptive lattice least squares algorithm is the use of scalar only operations, multiplications/divisions and additions, and the local communication which enables the development of a fully pipelining architecture. The tracking capability and the numerical stability and accuracy of the proposed technique are illustrated by simulations

Interpolating autoregressive processes: a bound on the restoration error

An upper bound is obtained for the restoration error variance of a sample restoration method for autoregressive processes that was presented by A.J.E.M. Janssen et al. (ibid., vol.ASSP-34, p.317-30, Apr. 1986). The upper bound derived is lower if the autoregressive process has poles close to the unit circle of the complex plane. This situation corresponds to a peaky signal spectrum. The bound is valid for the case in which one sample is unknown in a realization of an autoregressive process of arbitrary finite orde

A comparative overview of modal testing and system identification for control of structures

A comparative overview is presented of the disciplines of modal testing used in structural engineering and system identification used in control theory. A list of representative references from both areas is given, and the basic methods are described briefly. Recent progress on the interaction of modal testing and control disciplines is discussed. It is concluded that combined efforts of researchers in both disciplines are required for unification of modal testing and system identification methods for control of flexible structures

On issues of equalization with the decorrelation algorithm : fast converging structures and finite-precision

To increase the rate of convergence of the blind, adaptive, decision feedback equalizer based on the decorrelation criterion, structures have been proposed which dramatically increase the complexity of the equalizer. The complexity of an algorithm has a direct bearing on the cost of implementing the algorithm in either hardware or software. In this thesis, more computationally efficient structures, based on the fast transversal filter and lattice algorithms, are proposed for the decorrelation algorithm which maintain the high rate of convergence of the more complex algorithms. Furthermore, the performance of the decorrelation algorithm in a finite-precision environment will be studied and compared to the widely used LMS algorithm

Evaluating double and triple (?) boxes

A brief review of recent results on analytical evaluation of double-box Feynman integrals is presented. First steps towards evaluation of massless on-shell triple-box Feynman integrals within dimensional regularization are described. The leading power asymptotic behaviour of the dimensionally regularized massless on-shell master planar triple-box diagram in the Regge limit $t/s \to 0$ is evaluated. The evaluation of the unexpanded master planar triple box is outlined and explicit results for coefficients at 1/\ep^j, j=2,...,6, are presented.Comment: 6 pages, LaTeX with axodraw.sty; Talk presented at the International Symposium Radcor 2002 and Loops and Legs 2002 (September 8--13, Kloster Banz, Germany); to appear in Nuclear Physics B (Proc. Suppl.); a wrong abstract is replace

Improving parity games in practice

Parity games are infinite-round two-player games played on directed graphs whose nodes are labeled with priorities. The winner of a play is determined by the smallest priority (even or odd) that is encountered infinitely often along the play. In the last two decades, several algorithms for solving parity games have been proposed and implemented in PGSolver, a platform written in OCaml. PGSolver includes the Zielonka’s recursive algorithm (RE, for short) which is known to be the best performing one over random games. Notably, several attempts have been carried out with the aim of improving the performance of RE in PGSolver, but with small advances in practice. In this work, we deeply revisit the implementation of RE by dealing with the use of specific data structures and programming languages such as Scala, Java, C++, and Go. Our empirical evaluation shows that these choices are successful, gaining up to three orders of magnitude in running time over the classic version of the algorithm implemented in PGSolver