A theoretical analysis for the evaluation of the probability of error occuring in resampling a noise-like band-limited Gaussian signal with flat power spectrum available through its digitized samples, is presented. The analysis assumes the use of an ideal sinc-based interpolation algorithm for the digitized signal reconstruction, which is proved to be optimum for the considered class of signals and quantization functions. The particular case of lowest order, i.e., 1 bit, quantization function, is fully treated in analytical terms and a theoretical prediction for the error probability is derived. Validation of the presented analysis is made through a comparison with numerical simulations.
Lanucara, M., Borghi, R. (2007). Resampling of band-limited Gaussian random signals with flat power spectrum, available through 1-Bit quantized samples. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 55(8), 3987-3994 [10.1109/TSP.2007.894396].
Resampling of band-limited Gaussian random signals with flat power spectrum, available through 1-Bit quantized samples
BORGHI, Riccardo
2007-01-01
Abstract
A theoretical analysis for the evaluation of the probability of error occuring in resampling a noise-like band-limited Gaussian signal with flat power spectrum available through its digitized samples, is presented. The analysis assumes the use of an ideal sinc-based interpolation algorithm for the digitized signal reconstruction, which is proved to be optimum for the considered class of signals and quantization functions. The particular case of lowest order, i.e., 1 bit, quantization function, is fully treated in analytical terms and a theoretical prediction for the error probability is derived. Validation of the presented analysis is made through a comparison with numerical simulations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
