Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB(r) examples to emphasize the practical implementations both inside and outside the radar field.Section 3.3 will present an emerging dimensionality reduction technique known as random projections that have become ... data input space and as such, perform well when the underlying manifold is a linear or affine subspace of the input space. ... Efficient techniques such as the power method or EM algorithm can reduce.

Title | : | Sparse Representations for Radar with MATLAB Examples |

Author | : | Peter Knee |

Publisher | : | Morgan & Claypool Publishers - 2012 |

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