Current Trends in Signal Processing
Volume 4, Issue 2 (2014)
Published
Table of contents
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Study of ECG Signal Features Extraction using Wavelet Transform: A Review
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 …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 1–6 Read article
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Wavelets-based Denoising by Optimizing Polynomial Threshold Function
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 …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 11–23 Read article
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Embedded Real Time Operating Systems Performance Analysis for ARM7 Platform
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 …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 24–29 Read article
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Classification of Homogeneous and Heterogeneous Fog for Vision Enhancement
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 …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 7–10 Read article