University of York

• Abstract

  Compressive sensing (CS) and sparsity-aware techniques have demonstrated their effectiveness in the last few years for solving challenging signal processing problems in various applications in wireless Communications, electronic systems and sensor array; (AU)

  Knowledge-aided signal processing: theory, algorithms, implementation and applications, AP.R SPRINT

• Abstract

  This project aims to develop new ways to model complex network evolution, and will build on synergies between research at USP-Sao Carlos on network evolution and work at York on the spectral characterisation of graphs. In the first year of the project we will study how characterisations of graphs based on the eigenvalues and eigenvectors of the node-based Laplacian matrix evolve with time…

  Graph spectra and complex network evolution, AP.R

• Abstract

  Human leishmaniasis is an endemic disease distributed in tropical and subtropical regions of the world with an estimated 2 million new cases each year. The treatment of all clinical forms of leishmaniasis relies on costly parenteral administered drugs with multiple undesirable effects. Moreover, the first line drugs are becoming ineffective due to the proliferation of resistant parasites.…

  New approaches to combination chemotherapy for human leishmaniasis, AP.R

(Only some records are available in English at this moment)