Filtering of Audio Signals Using Discrete Wavelet Transforms

Abstract

Nonlinear diffusion has been proved to be an indispensable approach for the removal of noise in image processing. In this paper, we employ nonlinear diffusion for the purpose of denoising audio signals in order to have this approach also recognized as a powerful tool for audio signal processing. We apply nonlinear diffusion to wavelet coefficients obtained from different filters associated with orthogonal and biorthogonal wavelets. We use wavelet decomposition to keep signal components well-localized in time. We compare denoising results using nonlinear diffusion with wavelet shrinkage for different wavelet filters. Our experiments and results show that the denoising is much improved by using the nonlinear diffusion process.

High attenuation electromagnetic interface filter for effective processing of audio signals

“…The model created in MATLAB is implemented on a hardware board called Field programmable gate array (FPGA) board. FPGA boards have input output (I/O) block, configurable logic block (CLB), programmable switches, memory, registers and other peripheral devices [26]. FPGA helps in implementation of complex algorithms for real time signal and image processing [27].…”

“…Further implementation of the EMI filter will be extended for an analogue signal using an Omni-directional microphone embedded in mentioned Xilinx Nexys 4 Artix 7 FPGA board. The utilization of LUTs and slice registers are low compared to [26], it leads to minimize the hardware cost.…”