Two Stage Step-Size Adaptive Filter Design for ECG Denoising

An adaptive filter is a system that includes a linear filter with a converter controlled by input variables and the ability to change those parameters using an optimization technique. In the realm of noise cancellation, adaptive filter method is a large research area in the current decade. Adaptive filtering is required because real-time signals are always changing. The properties of an adaptive filter can be changed by modifying its parameter using an optimization algorithm triggered by the error signal. For some applications, adaptive processing is required because some variables of the desired production process (for example, the positions of reflected surfaces in a reverberation time space) are unknown or changeable. The closed - loop system adaptive filter refines its transfer function with data in the form of a signal. The Xilinx Virtex-5 series Field Programmable Gate Array (FPGA) technology is used to develop and implement a two-stage adaptive filter-based denoising architecture. The suggested adaptive two-stage adaptive filter’s performance is compared to that of the current Quantized Kernel Least Mean Square (QKLMS), Greatest Correntropy Criterion (MCC), and step size scalar adaptive filters. According to the findings, delay is decreased by 30.43 percent and area is raised by 31.37 percent in 4-Tap Architecture, and delay is decreased by 21.05 percent and area is expanded by 3.019 percent in 8-Tap Architecture. As a result, the delay is minimized, and the convergence rate is increased. As a result, it demonstrates the efficiency of the proposed designs in quickly de - noising ECGs in noise, demonstrating their applicability for lowish denoising applications in the medical area.