What is it about?

In this paper, the control theoretic smoothing spline is extended to robust and sparse splines via L1 optimality. The robustness is against outliers in data, while the sparsity is for representation of a curve with smaller number of parameters.

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Why is it important?

A control theoretic spline can be explained as drawing a curve with a robot hand. This illustrates that the control theoretic spline is a bridge between control and signal processing. Robust and sparse splines are important in large and complex systems, in particular, IoT (Internet of Things).

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This page is a summary of: ${L^1}$ Control Theoretic Smoothing Splines, IEEE Signal Processing Letters, November 2014, Institute of Electrical & Electronics Engineers (IEEE), DOI: 10.1109/lsp.2014.2337017.
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