Sparse Deconvolution Using Support Vector Machines Articles uri icon

publication date

  • June 2008

volume

  • 2008

International Standard Serial Number (ISSN)

  • 1687-6172

Electronic International Standard Serial Number (EISSN)

  • 1687-6180

abstract

  • Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution problems. Here, a sparse deconvolution algorithm based on the SVM framework for signal processing is presented and analyzed, including comparative evaluations of its performance from the points of view of estimation and detection capabilities, and of robustness with respect to non-Gaussian additive noise.