Computationally efficient adaptive rate sampling and filtering

This paper is a contribution to enhance the signal processing chain required in mobile systems. The system must be low power as it is powered by batteries. Thus a signal driven sampling scheme based on level crossing is employed, adapting the sampling rate and so the system activity by following the input signal variations. In order to efficiently filter the non-uniformly sampled signal obtained at the output of this sampling scheme a new adaptive rate FIR filtering technique is devised. The idea is to combine the features of both uniform and non-uniform signal processing tools to achieve a smart online filtering process. The computational complexity of the proposed filtering technique is deduced and compared to the classical FIR filtering technique. It promises a significant gain of the computational efficiency and hence of the processing power.