Current trends in signal processing (vol4, issue2) by STM Journals Publication

Current Trends in Signal Processing (CTSP)

ISSN: 2321-4252

May - August 2014

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I take the privilege to present the hard copy compilation for the [Volume 4 Issue (2)] of Journal of Current Trends in Signal Processing(CTSP). The intension of CTSP is to create an atmosphere that stimulates creativeness, research and growth in the area of Signal Processing. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. CTSP provides an outlet for Research findings and reviews in areas of Signal Processing found to be relevant for National and International recent developments & research initiatives. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain of Signal Processing. Finally, I express my sincere gratitude to the Editorial board members for their continuous support to bring this issue to its present form. Undoubtedly we could not release this issue without the amazing efforts of our Editors/Reviewers and Advisory board members. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra Director STM Journals

Current Trends in Signal Processing

Contents

1. Study of ECG Signal Features Extraction using Wavelet Transform - A Review Rishika Kaloniya, Sharda Vashisth, Pooja Sabherwal

2. Classification of Homogeneous and Heterogeneous Fog for Vision Enhancement Md. Imtiyaz Anwar, Arun Khosla

3. Wavelets-based Denoising by Optimizing Polynomial Threshold Function Rashmi Gupta, Hemant Tulsani

4. Embedded Real Time Operating Systems Performance Analysis for ARM7 Platform Vibhute Pritish M., Pawar Shitalkumar S.

Current Trends in Signal Processing ISSN: 2277-6176 (online), ISSN: 2321-4252 (print) Volume 4, Issue 2 www.stmjournals.com

Study of ECG Signal Features Extraction using Wavelet Transform: A Review Rishika Kaloniya*, Sharda Vashisth, Pooja Sabherwal Dept. of Electrical, Electronics and Communication Engineering, ITM University, Gurgaon, India

Abstract QRS-complex detection is used for analysis of ECG signal. ECG gives the information about electrical activity of the heart Since an ECG is a non-stationary signal and consists of various types of noise such as baseline wander, power line interference and muscle noise. To eliminate such types of noise wavelet transform is used. Mother wavelet is widely used to extract information from these types of signal by denoising. This paper gives the survey about the mother wavelet which is useful for denoising the ECG signals. The different mother wavelets compared and from that the more suitable mother wavelet is chosen.

Keywords: Heart, ECG, QRS complex, wavelet transform

Current Trends in Signal Processing ISSN: 2277-6176 (online), ISSN: 2321-4252 (print) Volume 4, Issue 2 www.stmjournals.com

Classification of Homogeneous and Heterogeneous Fog for Vision Enhancement Md. Imtiyaz Anwar*, Arun Khosla Department of ECE, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India Abstract Classification is the prior methodology to design vision enhancement algorithms to make them more efficient. In this reported work, mean intensity value and range of intensity level are proposed for the classification of camera images into homogeneous and heterogeneous fog due to turbid weather conditions for the first time. The use of average intensity and distribution of intensity of synthetic foggy images with different kind of fog are taken as reference to classify camera images. Proposed method is applicable to synthetic as well as camera foggy images. Simulation analysis shows that images with homogeneous fog have always higher mean intensity and narrow range of intensity level within a certain limit than heterogeneous fog.

Keywords: Classification, fog, mean intensity, homogeneous, heterogeneous

Current Trends in Signal Processing ISSN: 2277-6176 (online), ISSN: 2321-4252 (print) Volume 4, Issue 2 www.stmjournals.com

Wavelets-based Denoising by Optimizing Polynomial Threshold Function Rashmi Gupta*, Hemant Tulsani Ambedkar Institute of Advanced Communication Technologies and Research, New Delhi, India Abstract In this paper, a wavelets-based technique for denoising of one-dimensional signals is proposed which employs artificial bee colony (ABC) algorithm for optimizing a new polynomial threshold function. The coefficients of the threshold function are optimized dynamically to maximize the output signal to noise ratio (SNR). ABC algorithm calculates the coefficients for maximum output SNR. The proposed technique is tested for three artificial signals, namely blocks, bumps and Doppler signals. Additive white Gaussian noise (AWGN) is added to the signals and the results of denoising are presented. The results are compared with hard, soft and non-negative garrote threshold functions for three methods, VisuShrink, SUREShrink and MinMax, of determining threshold at different levels of decomposition. The performance of the algorithm is compared using different parameters such as input and output SNR, cross correlation coefficient and mean square error. The results show that the proposed algorithm provides better denoising results in all respects.

Keywords: Denoising, wavelet thresholding, polynomial threshold function, artificial bee colony algorithm

Current Trends in Signal Processing ISSN: 2277-6176 (online), ISSN: 2321-4252 (print) Volume 4, Issue 2 www.stmjournals.com

Embedded Real Time Operating Systems Performance Analysis for ARM7 Platform Vibhute Pritish M.*, Pawar Shitalkumar S. Department of E&TC, SRES COE, University of Pune, Kopargaon, Maharashtra, India Abstract An embedded RTOS is a software part of an embedded system that is used in the almost all the real-time application development process. It has a considerable effect on the reliability, robustness and performance of system under design and test. This paper addresses the concern of parameterized performance characteristics of two different RTOSs i.e. μC/OS-II and FreeRTOS ported on same common controller platform from ARM7TDMI family. Different OS services are identified and considered by performance parameters to establish performance metrics. Performance Metrics selected include Preemption time, context switching, interrupt latency and execution time. These parameters are further categorized into behaviour model and timing model for the need of abstractions. Concepts of parametric timing analysis were extended to consider the performance of the memory, processor and available peripherals.

Keywords: μC/OS-II, FreeRTOS.org, ARM7TDMI, LPC2148