{"product_id":"wavelet-shrinkage-models-for-denoising-of-biomedical-signals-von-poornachandra-s","title":"Wavelet Shrinkage Models for Denoising of Biomedical Signals","description":"\u003cp\u003eIn this thesis an efficient denoising models for  biological signals using shrinkage function and  shrikage based adaptive filters are addressed.  Signal denoising, an important problem of signal  processing aims to find an estimate of the original  signal from the noisy signal. There exist various  transform-domain algorithm based on performing  orthogonal transformation, modifying transforms  coefficients and inverse transforming the modified  transform coefficients. In this thesis, transform- domain signal denoising algorithm are equipped with  wavelet subband dependent threshold and prioritized  shrinkage. Hence they are made more adaptive to the  local variations of the signals, thus improving the  overall denoising efficiency. The main objective of  this work is to develop and implement a denoising  model for reducing the noises present in biological  signals such as ECE, EEG, PCG, Pulse, EMG etc., and  to eliminate the power line frequency interference  in these signals. The major work of this thesis is  developement of three new shrinkage functions  namely hyper, modified hyper and subband adaptive  shrinkage.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783838377087\"\u003e\u003ch3\u003eWavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783838377087","offer_id":39499093016669,"sku":"9783838377087","price":79.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/9b814e8b-3ca5-4f1b-abba-e69cdc7d0ae7.jpg?v=1768976320","url":"https:\/\/shop.autorenwelt.de\/products\/wavelet-shrinkage-models-for-denoising-of-biomedical-signals-von-poornachandra-s","provider":"Autorenwelt Shop","version":"1.0","type":"link"}