Design of hearing aid using novel similarity team algorithm in comparison with wavelet coefficient to improve accuracy

The primary objective is to develop more precise hearing aids by comparing the Similarity team method to wavelet coefficients. The primary goal of this study was to enhance precision by contrasting the similarity team technique with the wavelet coefficient. A total of 40 sample values are obtained from the dataset depicted in the graph and utilised to improve the precision of the hearing aid design. Group-1 (n=20) and Group-2 (n=10-20) classifications have been applied to these dataset values (20). The value of this sample was derived from the shaped frequency graph produced by denoising the raw, noisy data. The accuracy of the denoised raw file was improved by frequency shaping using a comparison of the Wavelet coefficient and the similarity team algorithm offered approach. When p is less than 0.05, the result is considered significant. The similarity team approach is shown to outperform wavelet coefficient on the dataset used in this study.