Now showing items 1-5 of 5

    • Affine projection subspace tracking 

      Vila Insa, Marc; López Molina, Carlos Alejandro; Riba Sagarra, Jaume (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference lecture
      Open Access
      In this paper, we consider the problem of estimating and tracking an R-dimensional subspace with relevant information embedded in an N-dimensional ambient space, given that N>>R. We focus on a formulation of the signal ...
    • Bootstrap signal processing: doing the impossible? 

      López Molina, Carlos Alejandro (Universitat Politècnica de Catalunya, 2018-06)
      Bachelor thesis
      Open Access
      Classical signal processing techniques are developed under prior statistical knowledge of the kind of data we are processing. Unfortunately, one does not know too much about reality in practice, therefore inferring information ...
    • Contributions to anomaly detection and correction in co-evolving data streams via subspace learning 

      López Molina, Carlos Alejandro (Universitat Politècnica de Catalunya, 2020-07)
      Master thesis
      12 months embargo
      During decades, estimation and detection tasks in many Signal Processing and Communications applications have been significantly improved by using subspace and component-based techniques. More recently, subspace methods ...
    • Estimation of information in parallel Gaussian channels via model order selection 

      López Molina, Carlos Alejandro; Cabrera Estanyol, Ferran de; Riba Sagarra, Jaume (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Conference lecture
      Open Access
      We study the problem of estimating the overall mutual information in M independent parallel discrete-time memory-less Gaussian channels from N independent data sample pairs per channel (inputs and outputs). We focus on the ...
    • NeAT: a nonlinear analysis toolbox for neuroimaging 

      Casamitjana Díaz, Adrià; Vilaplana Besler, Verónica; Puch Giner, Santi; Aduriz Saiz, Asier; Operto, Grégory; Cacciaglia, Raffaele; Falcón, Carlos; Molinuevo, José Luis; Gispert, Juan Domingo; López Molina, Carlos Alejandro (2020-03-25)
      Open Access
      NeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. ...