Reconfigurable Architecture for Noise Cancellation in Acoustic Environment Using Single Multiply Accumulate Adaline Filter

The creation of multiple applications with a higher level complexity has been made possible by the usage artificial neural networks (ANNs). In this research, an efficient flexible finite impulse response (FIR) filter structure called ADALINE (adaptive linear element) that makes use MAC (multiply accumulate) core is proposed. least mean square (LMS) and recursive (RLS) algorithms are most often used methods for maximizing coefficients. Despite outperforming LMS, RLS approach not favored real-time due to its design arithmetic complexity. To achieve less computation, fundamental utilized LMS-based tapping delay line filter, which practically workable option adaptive filtering algorithm. discover undiscovered system, adjustable coefficient filters have developed in suggested work utilizing optimal LMS approach. 10-tap being considered here analyzed synthesized field programmable gate array (FPGA) devices programming hardware description language. terms how well resources were used, placement postrouting performed well. If implemented architecture compared existing architecture, it reveals 25% decrease from one increase clock frequency roughly 20%.