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i-manager's Journal on Digital Signal Processing (JDP)

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Volume 3 Issue 4 October - December 2015

Research Paper

Dead Time Correction of Residence Time Distribution through Digital Signal Processing

Mohamed S. El_Tokhy* , Ibrahim M. Fayed, Mouldi A. Bedda*, H. Kasban****

- Department of Electrical Engineering, College of Engineering, Aljouf University, KSA.

Assistant Professor, Department of Electronics and Communication Engineering, College of Engineering, Aljouf University, KSA.

**** Department of Electrical Engineering, Nuclear Research Center, Atomic Energy Authority, Cairo, Egypt.

El_Tokhy,M.S., Fayed,I.M., Bedda,M.A., and Kasban.H. (2015). Dead Time Correction of Residence Time Distribution through Digital Signal Processing. i-manager's journal on Digital Signal Processing, 3(4), 1-8. https://doi.org/10.26634/jdp.3.4.3705

Abstract

This paper discusses the signal preprocessing of the acquired radiation signal for Residence Time Distribution (RTD). Radiation signals of Molybdenum-99 (Mo⁹⁹ ) were acquired through system setup. This system begins with a scintillator detector, channel counter and a Personal Computer (PC). Different forms of noise are accompanied with the RTD radiation signal. Consequently, an algorithm was proposed based on signal processing. This algorithm depends on background correction, base line restoration, statistical error computation, radioactive decay correction and dead time correction methods. Therefore, background correction was performed using two independent methods. These methods are the minimum value of the RTD radiation signal method and the subtraction method. Then, base line restoration was performed. Statistical error of the RTD radiation signal was computed. However, two different methods were studied for radioactive decay correction. Moreover, a dead time correction method is proposed. Therefore, dead time percent is obtained. Consequently, the number of lost pulses is investigated. The accuracy of the considered algorithm is determined based on statistical measurements of the acquired RTD signal. A remarkable accuracy of the dead time measurements is observed.

References

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Research Paper

Estimation of ECG Features Using Wavelet Analysis

Y. Dileep Kumar* , A.M. Prasad**

* Assistant Professor, Department of Electronics and Instrumentation Engineering, Sree Vidyanikethan Engineering College, Tirupathi, India.

** Professor & Head, Department of Electronics and Communication Engineering, JNTUK, Kakinada, India.

Kumar,D.Y., and Prasad.A.M. (2015). Estimation of ECG Features Using Wavelet Analysis. i-manager's journal on Digital Signal Processing, 3(4), 9-14. https://doi.org/10.26634/jdp.3.4.3706

Abstract

In previous days, acquiring and analysis of ECG signals can be done using different softwares. But in this work with the help of Wavelet analysis in LabVIEW software (Graphical programming software), it is easy to understand and use when compared to other softwares like MATLAB, C etc. To be in advance, they focused not only on acquiring and analysis of ECG signal, but also on identification of cardiac disorders. This system can be executed in three stages. In the first stage, the signal is preprocessed to remove the noise and onsets and the offsets are extracted. In the second stage, detection of peaks and in the third stage, cardiac disorders were estimated.

References

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Research Paper

Enhanced Fingerprint Image De-Noising Using Bi-Directional Recurrent Neural Network

Deepika Bancchor* , Siddharth Choubey**

*_** Shri Shankaracharaya Group of Institutions, Bhilai

Bancchor,D., and Choubey,S., (2015). Enhanced Fingerprint Image De-Noising Using Bi-Directional Recurrent Neural Network. i-manager's journal on Digital Signal Processing, 3(4), 15-19. https://doi.org/10.26634/jdp.3.4.3707

Abstract

Fingerprint Images (FPI) are always prone to be corrupted by various sources of noise during the capture of an image, i.e., acquisition period. This paper studies the implementation of Pixel Component Analysis (PCA) algorithm with Bi- Directional Recurrent Neural Network (BRNN) which will effectively de-noise the FPI images. BRNN enables compression of non-reusable fingerprint image data points during PCA execution and can transform vector co-ordinates in a rational manner. The duration of execution of the operation is also significantly reduced. The output of the proposed model has showed an optimized performance for de-noising of FPI images.

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Research Paper

Feature Extraction and Classification of ECG Signal Using Neuro-Wavelet Approach

Mayank Kumar Gautam* , V. K. Giri**

*-** Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Gautam,M,K., and Giri,V,K., (2015). Feature Extraction and Classification of ECG Signal Using Neuro-Wavelet Approach. i-manager's journal on Digital Signal Processing, 3(4), 20-26. https://doi.org/10.26634/jdp.3.4.3708

Abstract

The real wellspring of human misfortune in Cardiovascular Diseases (CVD) is Cardiac issues that are expanding step-bystep in the world. Incredible exertion is done to analyze the cardiovascular disease, where numerous individuals are utilized to the diverse sort of portable Electrocardiogram (ECG) using remote observing method. ECG Feature Extraction act as a critical part in diagnosing generally of the heart sicknesses. Presently a complete inspection has been done for highlighting the extraction of ECG sign dissecting, and extricating and finally characterizing have been arranged amid the long-prior time, and here the authors have presented delicate processing procedures. To perceive the current circumstance of the heart, Electrocardiography is a fundamental device however it is a period expending procedure to break down a persistent ECG signal as it might hold a huge number of relentless heart pulsates. Right now a simple sign can be converted in to a computerized one which helps in precisely diagnosing the sign. Point of this paper is to show an identification of some warmth arrhythmias utilizing the emerging neuro-wavelet approach.

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Review Paper

Space-Division Multiplexed Transmission over Few-Mode Fiber Based On Coherent MIMO Digital Signal Processing: A Review

Anuja Mishra* , Sharad Mohan Shrivastava, Pooja Sharma, Prachi Agrawal, Rahul Parganiha

,-* PG Scholar, Department of Communication Engineering, Vivekanand Technical University, Bhilai, India.

Assistant Professor, Department of Electronics & Telecommunication, Shri Shankaracharya Technical Campus Bhilai, India.

Mishra,A., Shrivastava,S,M., Sharma,P., Agrawal,P., and Parganiha,R., (2015). Space-Division Multiplexed Transmission over Few-Mode Fiber Based On Coherent MIMO Digital Signal Processing: A Review. i-manager's journal on Digital Signal Processing, 3(4), 27-36. https://doi.org/10.26634/jdp.3.4.3709

Abstract

The objective of this review paper is to make readers understand the key terms related to optical fiber specifically few mode fiber to help them carry out further research work. With the increasing demand for faster transmission systems, optical fiber communication system requirement is increasing day-by-day. As we know that the capacity limits of single mode fiber is almost reached its maxima, Space division multiplexing can be helpful for increasing the data rate requirement. This review paper, inferred the transmission of 6 spatial and polarisation modes, each carrying the quadrature-phase-shift-keyed channels over few-mode fiber keeping lower differential group delay. The detection of these channels is being carried out using coherent detection namely MIMO DSP. The 66 impulse response matrix representation of few-mode fiber is presented, revealing the coupling characteristics between the modes.

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