Rule-based Machine Learning Methods for Functional Prediction

We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision rules. A central objective of the method and representation is the induction of compact, easily interpretable solutions. This rule-based decision model can be extended to search efficiently for similar cases prior to approximating function values. Experimental results on real-world data demonstrate that the new techniques are competitive with existing machine learning and statistical methods and can sometimes yield superior regression performance.Comment: See http://www.jair.org/ for any accompanying file

Pretreatment method for anti-wettable materials

Anti-wettable materials brazing processes using titanium and zirconium for surface pretreatmen

Timbre-invariant Audio Features for Style Analysis of Classical Music

Copyright: (c) 2014 Christof Weiß et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Hopping conductivity in heavily doped n-type GaAs layers in the quantum Hall effect regime

We investigate the magnetoresistance of epitaxially grown, heavily doped n-type GaAs layers with thickness (40-50 nm) larger than the electronic mean free path (23 nm). The temperature dependence of the dissipative resistance R_{xx} in the quantum Hall effect regime can be well described by a hopping law (R_{xx} \propto exp{-(T_0/T)^p}) with p=0.6. We discuss this result in terms of variable range hopping in a Coulomb gap together with a dependence of the electron localization length on the energy in the gap. The value of the exponent p>0.5 shows that electron-electron interactions have to be taken into account in order to explain the occurrence of the quantum Hall effect in these samples, which have a three-dimensional single electron density of states.Comment: 5 pages, 2 figures, 1 tabl

On integrability of the differential constraints arising from the singularity analysis

Integrability of the differential constraints arising from the singularity analysis of two (1+1)-dimensional second-order evolution equations is studied. Two nonlinear ordinary differential equations are obtained in this way, which are integrable by quadratures in spite of very complicated branching of their solutions.Comment: arxiv version is already offcia

A performance comparison of fullband and different subband adaptive equalisers

We present two different fractionally spaced (FS) equalisers based on subband methods, with the aim of reducing the computational complexity and increasing the convergence rate of a standard fullband FS equaliser. This is achieved by operating in decimated subbands; at a considerably lower update rate and by exploiting the prewhitening effect that a filter bank has on the considerable spectral dynamics of a signal received through a severely distorting channel. The two presented subband structures differ in their level of realising the feedforward and feedback part of the equaliser in the subband domain, with distinct impacts on the updating. Simulation results pinpoint the faster convergence at lower cost for the proposed subband equalisers