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    Minimum-noise filter for baseline estimation in radiation detection systems.

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    Baseline height estimation in nuclear pulse spectrometry can be optimized by using a proper weight-function. The minimum-noise function for baseline estimation in presence of series and parallel white noises, constrained to a finite duration, is theoretically derived in this paper. Baseline restoration can be subsequently performed by subtracting the minimum-noise baseline estimation to the output signal pulse. The overall signal-to-noise performance obtained using the minimum-noise baseline estimation for pulse height correction is compared to that obtained with routinely used Base Line Restorers. An improvement of up to 16% in the Equivalent Noise Charge, with respect to classic baseline restoration, can be theoretically achieved in case of a simple triangular pulse shaping. The minimum-noise baseline weight-function can be synthesized in practice by means of a digital processing unit

    Design of high performance digital baseline restorers

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    In a modern radiation detection system, baseline restoration may be accomplished by means of a digital processor. We show that the performance of a well designed digital dc restorer significantly improves that of classic analog restorers, especially in case of high repetition rates. We present the basic design rules which permit to attain best results, while considering either a deterministic or a Poissonian statistic for pulse occurrence. We also show the very good agreement between theoretical and experimental results, which validates the analysis method
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