Roxana Smarandache

  1. LDPC Codes for Compressed Sensing.

    Authors: Roxana Smarandache, Alexandros G. Dimakis, Pascal O. Vontobel
    Subjects: Information Theory
    Abstract

    We present a mathematical connection between channel coding and compressed
    sensing. In particular, we link, on the one hand, \emph{channel coding linear
    programming decoding (CC-LPD)}, which is a well-known relaxation of
    maximum-likelihood channel decoding for binary linear codes, and, on the other
    hand, \emph{compressed sensing linear programming decoding (CS-LPD)}, also
    known as basis pursuit, which is a widely used linear programming relaxation
    for the problem of finding the sparsest solution of an under-determined system
    of linear equations.

  2. Decoding of Convolutional Codes over the Erasure Channel.

    Authors: Roxana Smarandache, Joachim Rosenthal, Virtudes Tomás
    Subjects: Information Theory
    Abstract

    In this paper we study the decoding capabilities of convolutional codes over
    the erasure channel. Of special interest will be maximum distance profile (MDP)
    convolutional codes. These are codes which have a maximum possible column
    distance increase. We show how this strong minimum distance condition of MDP
    convolutional codes help us to solve error situations that maximum distance
    separable (MDS) block codes fail to solve. Towards this goal, we define two
    subclasses of MDP codes: reverse-MDP convolutional codes and complete-MDP
    convolutional codes.

  3. Spectral Graph Analysis of Quasi-Cyclic Codes.

    Authors: Roxana Smarandache, Mark F. Flanagan
    Subjects: Information Theory
    Abstract

    In this paper we analyze the bound on the additive white Gaussian noise
    channel (AWGNC) pseudo-weight of a (c,d)-regular linear block code based on the
    two largest eigenvalues of H^T H. In particular, we analyze (c,d)-regular
    quasi-cyclic (QC) codes of length rL described by J x L block parity-check
    matrices with circulant block entries of size r x r.

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