Noise reduction and ECG feature extraction using interpolation and Hilbert transform

2014 ◽  
Author(s):  
S. Dhar ◽  
S. K. Mukhopadhyay ◽  
S. Mitra ◽  
M. M. Baig ◽  
M. Mitra
Keyword(s):  
Feature Extraction ◽  
Noise Reduction ◽  
Hilbert Transform

scholarly journals Fault feature extraction for rolling element bearing diagnosis based on a multi-stage noise reduction method

Measurement ◽  
2019 ◽  
Vol 139 ◽  
pp. 226-235 ◽  
Author(s):  
Junchao Guo ◽  
Dong Zhen ◽  
Haiyang Li ◽  
Zhanqun Shi ◽  
Fengshou Gu ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Noise Reduction ◽  
Reduction Method ◽  
Rolling Element Bearing ◽  
Multi Stage ◽  
Rolling Element ◽  
Element Bearing ◽  
Fault Feature Extraction

scholarly journals Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition

2010 ◽  
Vol 2010 ◽  
pp. 1-6 ◽  
Author(s):  
Emanuele Principi ◽  
Simone Cifani ◽  
Rudy Rotili ◽  
Stefano Squartini ◽  
Francesco Piazza
Keyword(s):  
Feature Extraction ◽  
Speech Recognition ◽  
Noise Reduction ◽  
Automatic Speech Recognition ◽  
Comparative Evaluation ◽  
Scientific Community ◽  
Additive Noise ◽  
Single Channel ◽  
Acoustic Conditions

One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms. Recently a certain attention has been paid to deeply integrate the noise suppressor in the feature extraction pipeline. In this paper, different single-channel MMSE-based noise reduction schemes have been implemented both in the frequency and cepstral domains and the related recognition performances evaluated on the AURORA2 and AURORA4 databases, therefore providing a useful reference for the scientific community.

A REVIEW OF IRIS RECOGNITION SYSTEM

2015 ◽  
Vol 77 (1) ◽  
Author(s):  
Arezou Banitalebi Dehkordi ◽  
Syed A. R. Abu-Bakar
Keyword(s):  
Feature Extraction ◽  
Image Compression ◽  
Quality Assessment ◽  
Noise Reduction ◽  
Iris Recognition ◽  
Image Acquisition ◽  
Recognition System ◽  
Biometric System ◽  
Large Database ◽  
Database Applications

Iris recognition system is an accurate biometric system. In recent years, iris recognition is developed to several active areas of research, such as; Image Acquisition, restoration, quality assessment, image compression, segmentation, noise reduction, normalization, feature extraction, iris code matching, searching large database, applications, evaluation, performance under varying condition and multibiometrics. This paper reviews a background of iris recognition and literature of recent proposed methods in different fields of iris recognition system from 2007 to 2015.

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