bullet Sensors & Transducers Journal

    (ISSN 1726- 5479)


2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2013

Editorial Calendar 2013

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents


Best Articles 2011




Vol. 157, Issue 10, October 2013, pp. 198-205




Online Multiscale Extraction of Signals by Using Wavelet Thresholding and Moving Window
Qibing Jin, * Sajid Khursheed

Beijing University of Chemical Technology No. 15, Bei San Huan East Road, Chaoyang Dist. Beijing, 100029, P. R. China
E-mail: sajid777@hotmail.com


Received: 11 July 2013   /Accepted: 25 September 2013   /Published: 31 October 2013

Digital Sensors and Sensor Sysstems


Abstract: By using the online multiscale extraction of signals and wavelet thresholding into a moving window of dyadic length, we can remove unpleasant or noise mistakes from the data. Genuine images are frequently corrupted by noise from various sources. It has been confirmed to have a better edge-preserving quality than linear filters in certain applications. Data extraction by univariate extraction is a well-known technique for processing in a correct simulation. Generally, linear filters are mainly smart in favor of on-line extraction of signals; however, those are single-scale in support of restoring information holding qualities in addition to noise with the reason of related choice in time and occurrence. Comparatively, nonlinear extraction methods, such as median-hybrid filters and wavelet segmentation are multiscale; however they may not be applied online, so in this paper, we have presented a new approach for online nonlinear extraction of signals by using moving window based on wavelet segmentation. Demonstrated figures show the results of online multiscale extraction of signals.


Keywords: Data extraction, Linear and non-linear extraction, Online multiscale extraction.


Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format



Download <here> the Library Journal Recommendation Form






1999 - 2018 Copyright , International Frequency Sensor Association (IFSA). All Rights Reserved.

Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn