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It is difficult to robustly estimate the parameters of an additive exponential model from a small number of frequency-domain measurements, especially when the model order is unknown and the parameters must be constrained to be real. Recent work in sparse sampling and sparse reconstruction casts this problem as a linear dictionary selection problem by densely sampling the parameter space. We present...
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