Computationally Efficient Adaptive Rate Sampling and Filtering

International audienceThe motivation of this work is to develop smart mobile systems. The goal is to reduce their power consumption by reducing theircomputational activity. Most of the real life signals are time varying in nature. Power efficiency can be achieved by adapting the system activity to the local variations of the input signal. 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 local variations. In order to efficiently filter the non-uniformly sampled signal obtained with 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. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. It promises a significant gain of the computational efficiency and hence of the processing power