Qualification: 
M.Tech
cb_rajesh@cb.amrita.edu

Rajesh C. B. currently serves as Assistant Professor at Department of Electronics and Communication Engineering, School of Engineering, Coimbatore Campus. He joined Amrita, Coimbatore Campus in 2008 and has more than 9 and half years service in Amrita. His areas of research include Embedded Systems and Image Processing.

Education

  • Pursuing: Ph. D. in Hyperspectral Image Processing
    Amrita Vishwa Vidyapeetham
  • 2005: Digital Electronics and Communication
    VTU/NMAMIT ,NITTE Karnataka
  • 2002: B. Tech. in Electronics Engineering
    Govt.Model Engineering College Ernakulam/ CUSAT

Professional Experience

Year Affiliation
July 2013 - Present Assistant Professor (Sr.Gr.), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham
Domain : Teaching, Class Advisor, Guiding Student Projects etc
July 1, 2011 – June 30, 2013 Assistant Professor, Amrita Vishwa Vidyapeetham
Domain :Teaching, Class Advisor, Guiding Student Projects etc
December 1, 2008 – June 30, 2011 Lecturer, Amrita Vishwa Vidyapeetham
Domain : Teaching, Class Advisor, Guiding Student Projects
July 25, 2005 – November 20, 2008 Lecturer, SNGCE Kadayiruppu,Kolencherry
Domain : Teaching,councilling
July 24, 2003 – September 18, 2003 Lecturer, College of Engineering, Poonjar
Domain : Teaching,councilling

Academic Responsibilities

SNo Position Class / Batch Responsibility
1. Class Adviser 2009 – 2013 ECE C Batch,2015 ECE B-Batch Continuing All the responsibilities related to that particular class (Councilling, Identifying the weak students, bridge the gap between the students and the subject handling faculties.)

Undergraduate Courses Handled

Academic Year Semester Name of the Subject Taught Tutorial/ Lab. Assistance/ Other Courses
Theory Practical
2018-2019 ODD Microprocessor and Microcontroller,Electronics Circuits I Microprocessor and Microcontroller Lab,Electronic Workshop Microprocessor and Microcontroller
2017-2018 Even Microprocessor and Microcontroller Microprocessor and Microcontroller Lab,Electronic Workshop Microprocessor and Microcontroller
ODD Embedded Systems Microprocessor and Microcontroller Lab,Electronic Workshop,Digital Systems Lab Embedded Systems  
2016-2017 ODD Microprocessors,Introduction to microcontrollers and its applications Microprocessor and Microcontroller Lab,Electronic Workshop  
EVEN Image Processing,Seminar Microprocessor and Microcontroller Lab,Electronic Workshop    
2015-2016 ODD Introduction to Microcontrollers and its applications Microcontroller Lab,Electronic Workshop  
Even Introduction to Embedded Systems Embedded Systems Lab    

Post-Graduate / PhD Courses Handled

  1. Embedded Systems (VLSI Design)
  2. Embedded Systems and DSP Architecture(VLSI Design)

Participation in Faculty Development / STTP / Workshops /Conferences

SNo Title Organization Period Outcome
1. Geoconnect 2018 "Advanced remote sensing technologies : Hyperspectral and LiDAR" IIST Trivandrum June 11 - 14, 2018 The workshop gave a good introduction to the field of hyper spectral image analysis and LiDar. This workshop was useful for more research openings .
2. 3DPCM : LiDAR point cloud processing with LAStools.One day workshop with hands-on training on 3D LiDAR point cloud processing and visualization with LAStools IIST Trivandrum October 12, 2017 The workshop gave a good introduction to point cloud processing with LAStools.One day workshop with hands-on training on 3D LiDAR point cloud processing and visualization with LAStools
3 Signals and Systems(BMWEE210x) IIT Bombay in blended mode July16, 2015 to December 18, 2015 To make aware the basic requirements of signals and systems course.
4 TA101 VERIFICATION COURSE ITAA July 9 - 10, 2015 Awareness in Teaching and learning.

Organizing Faculty Development / STTP / Workshops /Conferences

SNo Title Organization Period Outcome
1. ISRO Sponsored National Seminar onTechniques and Applications of Hyperspectral Image Analysis Amrita Vishwa Vidyapeetham University April 19-20, 2016 The seminar gave a good introduction to the field of hyper spectral image analysis, along with an insight into rich applications. This seminar was useful for more research openings and opportunities

Academic Research – PG Projects

SNo Name of the Scholar Programme Specialization Duration Status
1. SUJIT N R VLSI Design Testing and Verification 2014-15 Completed
2. RAJALAKSHMI T P VLSI Design Testing and Verification 2013-14 Completed
3 SANDEEP S VLSI Design Testing and Verification 2009-10 Completed

Publications

Publication Type: Journal Article

Year of Publication Title

2018

S. A., M., H. Sundar, S., S., M., N., and Rajesh C. B., “Classification of Arrhythmia using Wavelet Transform and Neural Network Model”, Journal of Bioengineering & Biomedical Science, vol. 8, no. 1, p. 244, 2018.[Abstract]


Cardiovascular diseases are a major cause of death. Change in normal human heart beat may result in different types of cardiac arrhythmias. An Irreversible damage to the heart is possible. In this paper a method is proposed to classify different arrhythmias and normal sinus rhythm, through a combination of wavelet Transform and Artificial Neural Networks (ANN) accurately and efficiently. Adaptive filtering using Recursive Least squares (RLS) adaptive algorithm is utilized to nullify AC and DC noises from the sample ECG signal set. ECG data’s are collected from MITBIH database. As ECG signal is a non- stationary signal wavelet transform is used to decompose the signal at various resolutions. This allows accurate detection and extraction of features. In our approach, discrete wavelet transforms (DWT) coefficients set is obtained from wavelet decomposition which would contain the maximum information about the arrhythmia. RR interval, QRS duration, PR duration is extracted from the wavelet decomposition. With these parameters classification of arrhythmia is done. Multilayer feed forward ANNs employ error back propagation (EBP) learning algorithm were trained and tested using the extracted parameters are used for training and testing the error back propagation (EBP) algorithm. Multilayer feed forward ANNs are employed through this EBP learning algorithm. This classification is done for 84 patient samples. The overall accuracy of our approach is 98.8%.

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Publication Type: Conference Paper

Year of Publication Title

2016

N. R. Sujit, Dr. Santhosh Kumar C., and Rajesh C. B., “Improving the Performance of Cardiac Abnormality Detection from PCG Signal”, in AIP Conference Proceedings, 2016, vol. 1715.[Abstract]


The Phonocardiogram (PCG) signal contains important information about the condition of heart. Using PCG signal analysis prior recognition of coronary illness can be done. In this work, we developed a biomedical system for the detection of abnormality in heart and methods to enhance the performance of the system using SMOTE and AdaBoost technique have been presented. Time and frequency domain features extracted from the PCG signal is input to the system. The back-end classifier to the system developed is Decision Tree using CART (Classification and Regression Tree), with an overall classification accuracy of 78.33% and sensitivity (alarm accuracy) of 40%. Here sensitivity implies the precision obtained from classifying the abnormal heart sound, which is an essential parameter for a system. We further improve the performance of baseline system using SMOTE and AdaBoost algorithm. The proposed approach outperforms the baseline system by an absolute improvement in overall accuracy of 5% and sensitivity of 44.92%

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2010

S. Sandeep and Rajesh C. B., “Differential Power Analysis on FPGA Implementation of MICKEY 128”, in Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010, Chengdu, 2010, vol. 9, pp. 667-671.[Abstract]


The MICKEY 128 (Mutual Irregular Clocking KEY stream generator with a 128-bit key) is a stream cipher designed in response to the ECRYPT 'Call for Stream Cipher Primitives' in 2005. For many applications, these implementations need to be resistant against side channel attacks, means; it should not be too easy to extract secret information from physical measurements on the device. This paper presents the results of differential power analysis attack against MICKEY 128 stream cipher hardware implementation. Our attack is targeted against an FPGA implementation of the MICKEY 128 on SPARTAN 3E.

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Publication Type: Conference Proceedings

Year of Publication Title

2014

T. P. Rajalakshmi and Rajesh C. B., “Low-Complexity Systolic Design for Finite Field Multiplier”, International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), 2014. 2014.[Abstract]


Here focus, is to implement a polynomial basis finite field multiplier. An area efficient systolic structure for finite field multiplication over the galois field GF(2m) based on irreducible polynomial was introduced. A novel cutest retiming can be introduced to reduce the critical path and thereby reduce the latency of operation. From the synthesis result from synopsys design vision and Xilinx, we find that the complexity of structure in terms of area, power and latency of the proposed structure can be reduced from the existing design.

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