Efficient mobile systems based on adaptive rate signal processing

Signal processing is an essential process in every mobile system. Standard signal processing is at a fixed rate, and it causes a pointless rise in system processing activity. Consequently, adaptive rate signal acquisition, segmentation, and denoising tactics are proposed. The system regulates parameters such as acquisition rate and denoising filter order by following the temporal disparities of the incoming signal, providing adequate tuning of the system processing activity. A speech database is employed to evaluate and compare the performance of the proposed solution with that of the traditional counter approach. Results demonstrate that the proposed method achieves a more than second order of magnitude gain over conventional counterparts while delivering a similar output quality. This confirms the benefit of integrating the designed solution into current mobile systems to improve their computational efficiency. (C) 2019 Elsevier Ltd. All rights reserved.