Saroja V.Siddamal

Work place: BVBCET/ECE, Hubli, 580021, India

E-mail: sarojavs@bvb.edu

Website:

Research Interests: Algorithm Design, Data Structures and Algorithms, Interaction Design, Computational Science and Engineering

Biography

Saroja V Siddamal, received the B.Tech. degree in Electronics and Communication Engineering, and M.E in Digital Electronics from Karnataka University, Dharwad in 1995 and 1997. She received Ph.D degree from Department of Electronics and Communication, the Jawaharlal Nehru Technology University at India in 2013. Presently she is serving as Associate Professor in Department of Electronics and Communication at B. V. Bhoomaraddi College of Engineering and Technology, Hubli. Her research interests include VLSI Signal Processing which includes Architectural design and BIST Testing. She advises doctoral students at Vishweshwaraya Technological University, Belgaum and Bangalore. She is faculty advisor for E-Baja 2015-2016, ESVC 2014-2016, HVVC -2015-2016 events. She has authored or co-authored over 25 technical papers in archival journals and refereed international conferences. She is the reviewer of many international conferences. She received best poster award in 2015 International Conference on Transformations in Engineering Education. She is life member of IETE and ISTE.

Author Articles
A Survey and Theoretical View on Compressive Sensing and Reconstruction

By Santosh S. Bujari Saroja V.Siddamal

DOI: https://doi.org/10.5815/ijigsp.2016.04.01, Pub. Date: 8 Apr. 2016

Most of the current embedded systems operate on digital domain even though input and output is analog in nature. All these devices contain ADC (Analog to Digital converter) to convert the analog signal in to digital domain which is used for processing as per the application. Images, videos and other data can be exactly recovered from a set of uniformly spaced samples taken at the Nyquist rate. Due to the recent technology signal bandwidth is becoming wider and wider. To meet the higher demand, signal acquisition system need to be improved. Traditional Nyquist rate which is used in signal acquisition suggests taking more numbers of samples to increase the bandwidth but while reconstruction most of the samples are not used. If samples are as per Nyquist rate then, this increases the complexity of encoder, storage of samples and signal processing. To avoid this new concept Compressive Sensing is used as an alternative for traditional sampling theory. This paper presents a survey and simplified theoretical view on compressive sensing and reconstruction and proposed work is introduced. 

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