Adaptive Rate Signal Acquisition and Denoising For Efficient Mobile Systems

The signal acquisition segmentation and de-noising are elementary processes, required in digital signal processing. The classical acquisition and denoising are time-invariant, the acquisition frequency and the de-noising module parameters remain fixed. It causes a pointless augmentation in the system processing load, particularly for the alternating signals. In this framework, adaptive rate signal acquisition and filtering method is devised. It is founded on a threshold traversing sampling and can correlate the acquisition rate, segmentation length and the denoising moduleparameters in accordance with the input signal temporal disparities. It renders an adaptation in the system processing activity according to the incoming signal temporal variations. The suggested system performance is evaluated for the speech signals. A performance comparison is also made with the traditional counterparts. Results demonstrate a radical computational gain, of the devised method over the traditional one, along with a similar output quality. It confirms the suitability of integrating the suggested solution in modern mobile systems in order to enhance their computational efficiency and power consumption.