i-manager Publications

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

Current Issue Vol. 12 Issue 1

Most Cited

Volume 4 Issue 2 April - June 2016

Research Paper

Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques

K. Purushotham Prasad* , B. Anuradha**

* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

Prasad,P.K., and Anuradha.B. (2016). Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques. i-manager’s Journal on Digital Signal Processing, 4(2), 1-7. https://doi.org/10.26634/jdp.4.2.5991

Abstract

The electrocardiogram (ECG) signal is a graphical recording of the electrical potentials generated in association with heart activity, which is one of the many important physiological signals commonly used in clinical practice. The wellbeing and status of a fetus can be accessed from a fetal ECG signal. Detecting and analysing the fetal ECG is the primary objective of electronic fetal monitoring. This paper presents a method to separate fetal ECG signals from the maternal abdomen. The method is general and is able to separate the fetal ECG signals using any number of recording electrodes, including the difficult case of single channel. This approach is based on some simple mathematical model using convolution matrix and with the help of maternal ECG, the fetal ECG signals can be extracted from the maternal abdomen. Further, the fetal ECG signals are passed through wavelets and adaptive filter to reduce the noise in the fetal ECG. The results show that the proposed method has a promising performance.

References

[1]. Reza Sameni and Gari D. Clifford, (2010). “A Review of Fetal ECG Signal Processing Issues and Promising Directions”. The Open Pacing, Electrophysiology & Therapy Journal, Vol. 3, No. 1, pp. 4-20.

[2]. R Swaranalatha and D.V. Prasad, (2010). “A Novel Technique for Extraction of FECG using Multi Stage Adaptive Filtering”. Journal of Applied Sciences, Vol. 10, No. 4, pp. 319-324.

[3]. R Swaranalatha and D.V. Prasad, (2009). “Interference Cancellation in FECG using waveletadaptive filtering Technique”. Journal of Engineering and Applied Sciences, Vol. 4(5-6), pp. 353-357.

[4]. Ravi Kumar Jatoth, Saladi S V K K Anoop, and CH Midhun Prabhu, (2009). “Biologically Inspired Evolutionary Computing tools for the Extraction of Fetal Electrocardiogram”. WSEAS Transactions on Signal Processing, ISSN: 1790-5052, Vol. 5, No. 3.

[5]. M. Sheikh M. Algunaidi, M. A. Mohd Ali, K. B. Gan, E. Zahedi, (2009). “Fetal Heart Rate Monitoring Based on Adaptive Noise Cancellation and Maternal QRS Removal Window”. European Journal of Scientific Research, Vol. 27, No. 4, pp. 565-575.

[6]. Congenital Heart Defects in Children Fact Sheet, 2008. Retrieved from: http: //www.americanheart.org/ children

[7]. Sameni R, Clifford GD, Jutten C, and Shamsollahi MB., (2007). “Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals”. EURASIP J. on Adv. Signal Processing, pp. 1-14.

[8]. Michael GF, Philip AR, Frederick J, et al., (2006). Physiology. Retrieved from http: //www.cardioconsult. com/Physiology/

[9]. EC Karvounis, C Papaloukas, DI Fotiadis, and LK Michalis, (2004). “Fetal Heart Rate Extraction from Composite Maternal ECG Using Complex Continuous Wavelet Transform”. Computers in Cardiology, Vol. 31, pp. 737-740.

[10]. F. Mochimaru, Y. Fujimoto and Y. Ishikawa, (2002). “Detecting the Fetal Electrocardiogram by Wavelet Theor y-Based Methods”. Progress in Biomedical Research, Vol. 7, No. 3.

[11]. Peters M., Crowe J., Piéri J., (2001). “Fetal Monitoring the Fetal Heart Non-Invasively: A Review of Methods”. J. Perinat. Med., Vol. 29, pp. 408-16.

Full Article (HTML)

Pdf

Research Paper

An Approach of ECG Analysis for Diagnosis of Heart Diseases

Ekta Gajendra* , Jitendra Kumar**

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India.

** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

Gajendra,E., and Kumar,J. (2016). An Approach of ECG Analysis for Diagnosis of Heart Diseases. i-manager’s Journal on Digital Signal Processing, 4(2), 8-16. https://doi.org/10.26634/jdp.4.2.5993

Abstract

In Today's World, heart problems are the major health concern people are facing. In order to prolong life, one must be fit and should keep a check on their health. Cardiac Arrhythmia is one such heart condition, which can be diagnosed from the persons ECG (Electrocardiogram). ECG is the graphical representation of the heart's electrical activity. Any change in the waveform of the ECG depicts change in the functioning of it, which can be used as a diagnostic measure. ECG Classification is done in 3 stages, first is de-noising of the ECG signal, in the second step, the authors perform feature Extraction and finally Classifies it. The authors use FIR Filter for signal de-noising and then, they have tried to do the analysis using DOM (Difference Operation Method) for feature extraction and LDA (Linear Discriminant Analysis) for the classification of ECG signal to predict if he/she is vulnerable to any such heart condition or not. On using the above named methods the authors achieve an accuracy of 98.077% and a sensitivity of 98.009%.

References

[1]. Ouelli, A., Elhadadi, B. and Bouikhalene, B., (2014). “Multivariate Autoregressive Modeling for Cardiac Arrhythmia Classification Using Multilayer Perceptron Neural Networks”. IEEE, pp. 402-406.

[2]. Pathoumvanh, S., Hamamoto, K. and Indahak, P. (2014). “Arrhythmias Detection and Classification Base On Single Beat Ecg Analysis”. 4^th Joint International Conference on Information and Communication Technology, Electronic and Electrical Engineering (JICTEE). 978-1-4799-3854-4, pp. 1-4.

[3]. Ahmed, R., and Arafat, S., (2014). “Cardiac Arrhythmia Classification using Hierarchical Classification Model”. 6^th International Conference on CSIT, pp. 203- 207.

[4]. Klaynin, P., Wongseree, W., Adisorn Leelasantitham, A., and Kiattisin, S., (2013). “An Electrocardiogram Classification Method based on Neural Network”. Biomedical Engineering International Conference, pp. 1- 4.

[5]. Kamaruddin, N.H., Murugappan, M., and Omar, M.I. (2012). “Early Prediction of Cardiovascular Diseases using ECG Signal: Review”. IEEE, Student Conference on Research and Development, pp. 48-53.

[6]. Das, M.K., Ghosh, D.K., and Ari, S., (2013). “Electrocardiogram (ECG) Signal Classification Using S-Transform, Genetic Algorithm And Neural Network”. IEEE 1^st International Conference on Condition Assessment Techniques in Electrical Systems, pp. 353-357.

[7]. Bushra Mehdi, B., Tahmina Khan, T., and Ali, Z.A., (2013). “Artificial Neural Network Based Electrocardiography Analyzer”. IEEE, pp.1-7.

[8]. Faziludeen, S., and Sabiq P.V., (2013). “ECG Beat Classification Using Wavelets And SVM”. IEEE Conference on Information and Communication Technologies, pp. 815-818.

[9]. Abibullaev, B., Kang, W.S., Lee, S.H., and Jinung An, (2010). “Classification of Cardiac Arrhythmias Using Bi- Orthogonal Wavelet Preprocessing and SVM”. IEEE, pp. 1- 5.

[10]. Pingale, S.L., and Daimiwal, N., (2010). “Detection Of Various Diseases Using Ecg Signal In MATLab”. International Journal of Recent Technology and Engineering, Vol. 3, No. 1, pp. 1-5.

[11]. Mohamad, F.N., M. S. A. Megat Ali, A. H. Jahidin, M. F. Saaid, and M. Z. H. Noor, (2013). “Principal Component Analysis And Arrhythmia Recognition Using Elman Neural Network”. IEEE 4^th Control and System Graduate Research Colloquium, pp. 19-20 .

[12]. Ali, M.S.A.M., Jahidin, A.H., and Norali, A.N. (2012). “Hybrid Multilayered Perceptron Network For Classification of Bundle Branch Blocks”. International Conference on Biomedical Engineering (ICOBE), pp. 149-154.

[13]. Rao, S., Jadhav. M., Nalbalwar, S. L., and Ghatol, A.A. “Generalized Feed forward Neural Network Based Cardiac Arrhythmia Classification From ECG Signal Data”. IEEE, pp. 351 – 356.

[14]. Karpagachelvi, S., Arthanari, M., and Sivakumar, M. (2010). “ECG Feature Extraction Techniques - A Survey Approach”. (IJCSIS), International Journal of Computer Science and Information Security, Vol. 8, No. 1.

[15]. Emanet, N. (2009). “ECG Beat Classification By Using Discrete Wavelet Transform And Random Forest Algorithm”. IEEE, ICSCCW 2009, pp. 1-4.

[16]. Khan, T.T., Sultana, N., Reza, R.B., and Mostafa, R. (2015). “ECG Feature Extraction in Temporal Domain and Detection of Various Heart Conditions”. ICEEICT, pp. 1-6.

[17]. Sahoo, S.K., Subudhi, A.K., Kanungo, B., and Sabut, S.K. (2015). “Feature Extraction of ECG Signal based on Wavelet Transform for Arrhythmia Detection”. IEEE, pp. 1-5.

[18]. Sujan, K.S.S., Priya, K.P., Pridhvi, R.S., and Ramana, R.V. (2015). “Performance analysis for the Feature extraction algorithm of an ECG signal”. ICIIECS.

[19]. Saminu, S., Özkurt, N., and Karaye, I.A. (2014). “Wavelet Feature Extraction for ECG Beat Classification”. IEEE 6^th International Conference on Adaptive Science and Technology (ICAST), pp. 1-6.

[20]. Muthuvel, K., Suresh, L.P., Veni, S.H.K., Kannan, K.B. (2014). “ECG Signal Feature Extraction and Classification using Harr Wavelet Transform and Neural Network”, ICCPCT, pp. 1396-1399.

[21]. Biswas, U., Das, A., Debnath, S., and Oishee, I., (2014). “ECG Signal Denoising by Using Least-Mean- Square and Normalised-Least-Mean-Square Algorithm Based Adaptive Filter”. 3^rd International Conference On Informatics, Electronics & Vision, pp. 1-6.

[22]. Zhang, N., Nie, Z., Luo, Y., Du, L., Wang, X., and Wang, L., (2014). “A Reconfigurable Overlapping FFT/IFFT Filter for ECG Signal De-noising”. International Symposium on Bioelectronics and Bioinformatics IEEE, pp. 1-4.

[23]. Biswas, U., and Maniruzzaman, M., (2014). “Removing Power Line Interference from ECG Signal Using Adaptive Filter and Notch Filter”. ICEEICT.

[24]. Hashim, F.R., Soraghan, J.J., Petropoulakis, L., and Daud, N.G.N., (2014). “EMG Cancellation from ECG Signals using Modified NLMS Adaptive Filters”. IEEE Conf. on Biomedical Engineering and Sciences (IECBES), pp. 735-739.

[25]. Gaikwad, K.M., and Chavan, M.S., (2014). “Removal of High Frequency Noise from ECG Signal Using Digital IIR Butterworth Filter”. GCWCN IEEE, pp. 121-124.

[26]. Niederhauser, T., Marisa, T., Kohler, L., Haeberlin, A., Wildhaber, R.A., Abächerli, R., Goette, J., Jacomet, M., and Vogel, R. (2015). “A Baseline Wander Tracking System for Artifact Rejection in Long-Term Electrocardiography”, IEEE Trans.Biomed.Circuits syst., pp. 255-265.

[27]. Gordillo, L.A., Medina-Santiago A. Zepeda- Hernandez J. Hernandez-De Leon H. Reyes Barranca M.A , (2014) . “An Adaptive Geometrically-Complemented Approach for ECG Signal Denoising”. CCE, pp. 1-6.

[28]. Bhogeshwar, S.S., Soni, M.K., Bansal, D., (2014). “Design of Simulink Model to denoise ECG signal using various IIR & FIR filters”. ICROIT.

[29]. Mehala, N., and Anand, (2013). “IIR Multiple Notch Filter Design for Power Line Interference Removal”. IJESE, Vol. 1, No. 10, pp. 65-68.

[30]. Chavan, M.S., Agarwala, R., and Uplane, M.D., (2008). “Design and implementation of Digital FIR Equiripple Notch Filter on ECG Signal for removal of Power line Interference”. WSEAS Transactions on Signal Processing, Vol. 4, No. 4, pp. 221-230.

[31]. Smart Cooky, (2014). World Heart Day 2014: Is India staring at a Heart Disease Epidemic.

[32]. Physionet.org. Physio Bank ATM. Retrieved from http://physionet.org/cgi-bin/atm/ATM

[33]. Yeh, Y.C., Wang, W.J., Chiou, C.W., (2009). “Cardiac Arrhythmia Diagnosis Method Using Linear Discriminant analysis on ECG signals”. Measurement, Vol. 42, pp. 778–789.

[34]. Lin, L.C., Yeh, Y.C., and Chu, T.Y., (2014). “Feature Selection Algorithm for ECG Signals and Its Application on Heartbeat Case Determining”. International Journal of Fuzzy Systems, Vol. 16, No. 4.

[35]. Hampton, J.R. The ECG Made Easy, Sixth Edition. pp. 7-12.

[36]. Hampton, J.R. The ECG in Practise, Fourth Edition, pp.1-3.

[37]. Phycionet.org. Physio Bank Annotations. Retrieved from https://www.physionet.org/physiobank/annotations. shtml

Full Article (HTML)

Pdf

Research Paper

A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB

Manjinder Kaur* , Sangeet Pal Kaur**

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Kaur,M., and Kaur,S,P. (2016). A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB. i-manager’s Journal on Digital Signal Processing, 4(2), 17-23. https://doi.org/10.26634/jdp.4.2.5994

Abstract

This paper presents a new window for designing FIR low pass filter. While designing a FIR filter, there are two important parameters which must be taken care of which are transition width and ripples. Transition width should be as small as possible and ripples should be less both in pass band as well as stop band. There are different windows like Rectangular, Triangular, Hanning, Hamming, Blackman, etc., which are used for filter designing. The proposed window which is a modified form of Blackman window contains four cosine parameters and the simulation result shows that this window has better response when compared to Blackman Window.

References

[1]. Alan V. Oppenheim & Ronald W. Schafer, (1999). Discrete-Time Signal. Second Edition, Prentice-Hall, pp. 491-492.

[2]. John G. Proakis, Dimitris G. Manolakis, (2007). Digital Signal Processing Principals, Algorithms and Application. th 4 Edition, Prentice-Hall, pp. 654-655.

[3]. P. Ramesh Babu, (2013). Digital Signal Processing. 4 Edition, Scitech Publications (India) Pvt. Ltd.,Chennai, pp. 5.1-5.2

[4]. Zhenhe Sun, Wei Yu, Chen He, (2012). “FIR digital filter design and MATLABsimulation”. IEEE, International Conference on Measurement, Information and Control(MIC), pp. 677-680, May 18-20.

[5]. Sonika Gupta, Aman Panghal, (2012). “Performance Analysis of FIR Filter Design by Using Rectangular, Hanning and Hamming Windows methods”. International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 6.

[6]. Rick M. Roark, (2000). “Design of FIR Filters with Exceptional Passband and Stopband Smoothness using a New Transitional window”. IEEE, International Symposium on Circuits and Systems, Geneva, Switzerland, pp. 96-99, May 28-31.

[7]. Subhadeep Chakraborty, (2013). “Advantages of Blackman Window over Hamming Window method for designing FIR filter”. International Journal of Computer Science& Engineering Technology, Vol. 4, No. 8, ISSN : 2229-3345.

[8]. Alia Ahmed Eleti and Amer R. Zerek, (2013). “FIR Digital Filter Design By Using Windows Method With MATLAB”. IEEE, th 14 international Conference on Sciences and Techniques of Automatic Control & Computer Engineering, Sousse, Tunisia, pp. 282-287, December 20- 22.

[9]. B. S. Nair, Digital Signal Processing Theory, Analysis and th Digital-filter Design. 6 Edition, PHI Learning Private Limited, New Delhi.

[10]. S. K. Mitra, (2005). Digital Signal Processing, New York: Tata McGraw Hill.

[11]. http://www.dspguide.com/ch21/2.htm

Full Article (HTML)

Pdf

Research Paper

Image Edge Preserving Filter with Impulse Noise Detection and Removal

Neelima* , Pankaj Mohindru, Pooja Mohindru*

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

-* Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

Neelima., Mohindru,P., and Mohindru,P. (2016). Image Edge Preserving Filter with Impulse Noise Detection and Removal. i-manager’s Journal on Digital Signal Processing, 4(2), 24-33. https://doi.org/10.26634/jdp.4.2.5995

Abstract

This paper illustrates a new non-linear image edge-preserving filter, used for the detection and elimination of immense frequency impulse noise from digital images. Schemed method subsists of two stages i.e., pixel position detection and filtering. Simulation analysis has been performed on distinct images and results have been demonstrated in comparison to some previously designed filters. The proposed scheme works in a satisfactory way even upon noise densities in a high range of 95% to 97% in both visual presentation and quantitative measures. This designed filter preserves the edges of images with high degree of accuracy. Performance parameters such as PSNR, MAE, RMSE, and SSIM are better than most of the schemes currently in use.

References

[1]. P. Siva Kumar, K. Sriknivasan, and M. Rajaram, (2010). “Performance Evaluation of Statistical Based Median Filter to Remove Salt and Pepper Noise”. Second International Conference on Computing, Communication and Networking Technologies.

[2]. Manika Gupta, Beant Kaur, and Garima Saini, (2015). “Slotted Multi-band PIFA for Wireless Applications”. imanager’s Journal on Wireless Communication Network, Vol. 4, No. 3, pp. 22 - 26.

[3]. Astola J, and Kuosmanen P, (1997). Fundamentals of on Linear Digital Filtering. CRC Press, Boca Raton.

[4]. Yin. L, Ruikang Yang, Moncef Gabbouj, and Y. Neuvo, (1996). “Weighted Median Filters”. IEEE Trans Circuits Syst II., Vol. 43, No. 3, pp. 157 - 192.

[5]. Lee Y.H., (1991). “Center Weighted Median Filters and Their Applications to Image Enhancement”. IEEE Trans Circuits Syst., Vol. 38, No. 9, pp. 984 - 993.

[6]. Wang Z, and Zhang D.,(1996). “Progressive Switching Median Filter for The Removal of Impulse Noise From Highly Corrupted Images”. IEEE Trans Circuits Syst II., Vol. 46, No. 1, pp. 78 - 80.

[7]. Srinivasan K.S, and Ebenezer D, (2007). “A New Fast and Efficient Decision-Based Algorithm for Removal of High Density Impulse Noises”. IEEE Signal Process Lett., Vol. 14, No. 3, pp. 189 - 192.

[8]. E.S. Veerakumar T., Subramanyam A. N., and Premchand C. H., (2011). “Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter”. IEEE Signal Process Lett., Vol. 18, No. 5, pp. 287 - 290.

[9]. Haidi I., Nicholas S. P. K., and Theam F. N., (2008). “Simple Adaptive Median Filter for Removal of Impulse Noise From Highly Corrupted Images”. IEEE Trans Consum Electronics, Vol. 54, No. 4, pp. 1 - 3.

[10]. V.R. Vijay Kumar, G. Santhana Mari, and D. Ebenezer, (2014). “Fast Switching Based Median-Mean Filter for High Density Salt and Pepper Noise Removal”. International Journal of Electronics and Communications, Vol. 68 , pp. 1145 -1155.

Full Article (HTML)

Pdf

Research Paper

Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP

Anuja Mishra* , Sharad Mohan Shrivastava**

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

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

Mishra,A., and Shrivastava,S,M. (2016). Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP. i-manager’s Journal on Digital Signal Processing, 4(2), 34-42. https://doi.org/10.26634/jdp.4.2.5996

Abstract

Next-generation communication evolution towards 4G promises to meet the demands for ubiquitous communication. MIMO technology convolved with Optical fiber has become a mandatory requirement to achieve the goals of future communications. This paper describes the System design methodology for MIMO DSP platform. Software simulations provide flexibility, hence the authors simulate results using a software named “Optiwave's Optisystem”. The authors propose a transmission fiber for mode-division multiplexed transmission with multiple-input multiple-output (MIMO) digital signal processing supporting six spatial and polarisation modes. To increase the transmission capacity of fewmode fiber (FMF) drastically, Wavelength-Division Multiplexing Mode-Division Multiplexing (WDM-MDM), an optical MIMO technique, can be applied. With WDM-MDM, different mode groups, propagating in FMF are used to carry different information.

References

[1]. R. Tkach, (2010). “Scaling Optical Communications for the Next Decade and Beyond”. Bell Labs Technical Journal, Vol.14 ,No.4, pp.39.

[2]. R. J. Essiambre, G. Kramer, P. J. Winzer, G. J. Foschini, and B. Goebel, (2010). “Capacity Limits of Optical Fiber Networks”. J. Lightwave Technol, Vol. 28, No. 4, pp. 662- 701.

[3]. A. Chraplyvy, (2009). “The Coming Capacity Crunch”. Proc. European Conf. on Opt. Commun. (ECOC), Planary Talk.

[4]. P. J. Winzer (2011). “Energy-Efficient Optical Transport Capacity Scaling Through Spatial Multiplexing”. Photon. Technol. Lett. Vol. 23, No. 13, pp. 851-853.

[5]. S. Berdague and P. Facq (1982). “Mode Division Multiplexing in Optical Fibers”. Appl. Opt. Vol. 21, No. 11, pp. 1950 1955.

[6]. M.de Boer, C. P.Tsekrekos, A. Martinez, H. Kurniawan, J. W. M. Bergmans, A. M. J. Koonen, H. P. A.van den Boom, and F. M. J. Willems, (2005). “A First Demonstrator for a Mode Group Diversity Multiplexing Communication System”. In Proc. IEEE Seminar Ref Optical Fibre Communications and Electronic Signal Processing.

[7]. S. Schollmann, S. Soneff, and W. Rosenkranz, (2007). “10.7 Gb/s over 300 m GI-MMF using a 2x2 MIMO system based on mode group diversity multiplexing”. In Proc. Conf. Optical Fiber Communication and the National Fiber Optic Engineers Conf. OFC/NFOEC 2007, pp.1-3.

[8]. A. R. Shah, R. C. J. Hsu, A. Tarighat, A. H. Sayed and B.Jalali, (2005). “Coherent Optical MIMO (COMIMO)”. J. Lightwave Technol., Vol.23, No.8, pp. 2410-2419.

[9]. A.Li, A. Al Amin, X. Chen and W. Shieh, (2011). “Reception of Mode and Polarization Multiplexed 107Gb/s CO-OFDM Signal Over a Two-Mode Fiber”. Proc. Opt. Fiber Commun. Conf. (OFC), PDPB8.

[10]. M. Salsi, C. Koebele, D. Sperti, P. Tran, P. Brindel, H. Mardoyan, S. Bigo, A. Boutin, F. Verluise, P. Sillard, M. Bigot Astruc, L. Provost, F. Cerou and G. Charlet, (2011). “Transmission at 2100Gb/s, Over Two Modes of 40 km-long Prototype Few-Mode Fiber, Using LCOS Based Mode Multiplexer and Demultiplexer ”. Proc. Opt. Fiber Commun. Conf. (OFC), PDPB9.

[11]. N. Hanzawa, K. Saitoh, T. Sakamoto, T. Matsui, S. Tomita, and M. Koshiba, (2011). “Demonstration of Mode- Division Multiplexing Transmission over 10 km Two-Mode Fiber with Mode Coupler”. Proc. Opt. Fiber Commun. Conf. (OFC).

[12]. R. Ryf, S. Randel, A. H. Gnauck, C. Bolle, A. Sierra and S. Mumtaz, M. Esmaeelpour, E. C. Burrows, R. J. Essiambre, P. J. Winzer, D. W. Peckham, A. McCurdy, and R. Lingle (2011). “Mode-Division Multiplexing Over 96 km of Few-Mode Fiber Using Coherent 66 MIMO processing”. J. Lightwave Technol., Special Issue about OFC/NFOEC .

[13]. E. Ip, N. Bai, Y. K. Huang, E. Mateo, F. Yaman, M. J. Li, S. Bickham, S. Ten, J. Linares, C. Montero, V. Moreno, X. Prieto, V. Tse, K. M. Chung, A. Lau, H. Y. Tam, C. Lu, Y. Luo, G. D. Peng and G. Li, (2011). “883112-gb/s WDM Transmission Over 50 km of Three-Mode Fiber with Inline Few-Mode Fiber Amplifier”. Proc. European Conf. on Opt. Commun. (ECOC).

[14]. C. Koebele, M. Salsi, L. Milord, R. Ryf, C. Bolle, P. Sillard, S. Bigo and G. Charlet, (2011). “40 km Transmission of Five Mode Division Multiplexed Data Streams at 100Gb/s with Low MIMODSP Complexity”. Proc. European Conf. on Opt. Commun, (ECOC).

[15]. P. J. Winzer and C. J. Foschini, (2011). “MIMO Capacities and Outage Probabilities in Spatially Multiplexed Optical Transport Systems”. Optics Express, Vol. 19, No. 17, pp. 16680-16696.

[16]. G. Keiser (2000). Optical Fiber Communications, 3 Ed. New York: Mc- Graw Hill.

[17]. D. Marcuse (1991). Theory of Dielectric Optical Waveguides, P. F. Liao and P. L. Kelley, Eds. New York: Academic.

[18]. W. Q. Thornburg, C. B. J. and X. D. Zhu, (1994). “Selective Launching of Higher-Order Modes into an Optical Fiber with an Optical Phase Shifter”. Opt. Lett. Vol. 19, No. 7, pp.454-456.

[19]. W. Mohammed, M. Pitchumani, A. Mehta and E. G. Johnson, (2006). “Selective Excitation of the LP Mode in 11 Step Index Fiber Using a Phase Mask”. Optical Engineering, Vol. 45, No. 7, pp.074-602.

[20]. Y. Awaji, N. Wada, and Y. Toda, (2010). “Demonstration of Spatial Mode Division Multiplexing Using Laguerre Gaussian Mode Beam in Telecom rd Wavelength”. In Proc. IEEE 23 Annu. Meet. Photon. Soc., pp. 551-552.

[21]. J. Salz (1985). “Digital Transmission Over Cross- Coupled Linear Channels”. ATnT Tech. J., Vol. 64, pp. 1147-1159.

[22]. S. Randel, R. Ryf, A. Sierra, P. J. Winzer, A. H. Gnauck, C. A. Bolle, R. J. Essiambre, D. W. Peckham, A. McCurdy, and R. Lingle, (2011). “656Gb/s Mode-Division Multiplexed Transmission Over 33km Few-Mode Fiber Enabled by 6x6 MIMO Equalization, Opt. Exp., Vol. 19, No. 17, pp. 16697-16707.

[23]. Roland Ryf, Sebastian Randel, Rene- Jean Essiambre and Peter J. Winzer, (2012). “Space-Division Multiplexed Transmission Over Few-Mode and Coupled- Core Fiber Based on Coherent MIMO Digital Signal Processing”. Bell Labs Technical Planary Paper.

[24]. A. Sierra, S. Randel, P. J. Winzer, R. Ryf, A. H. Gnauck and R. J. Essiambre, (2012). “On the use of delay decorrelated I/Q test sequences for QPSK and QAM signals”. Photon. Technol. Lett, Vol. 24, No. 12, pp. 1000- 1002.

[25]. Anuja Mishra, Sharad Mohan Shrivastava, Pooja Sharma, Prachi Agrawal and Rahul Parganiha, (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, Vol. 3, No. 4.

[26]. Anuja Mishra, Sharad Mohan Shrivastava, Pooja Sharma, Prachi Agrawal and Rahul Parganiha, (2016). “Mode-Division Multiplexing Over Few-Mode Fiber Using Coherent MIMO Digital Signal Processing”. i-manager’s Journal on Digital Signal Processing, Vol. 4, No. 1.

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

Current Issue Vol. 12 Issue 1

Most Read

Most Cited

Volume 4 Issue 2 April - June 2016

Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques

K. Purushotham Prasad* , B. Anuradha**

* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India. ** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

Prasad,P.K., and Anuradha.B. (2016). Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques. i-manager’s Journal on Digital Signal Processing, 4(2), 1-7. https://doi.org/10.26634/jdp.4.2.5991

Abstract

References

Full Article (HTML)

Pdf

An Approach of ECG Analysis for Diagnosis of Heart Diseases

Ekta Gajendra* , Jitendra Kumar**

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India. ** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

Gajendra,E., and Kumar,J. (2016). An Approach of ECG Analysis for Diagnosis of Heart Diseases. i-manager’s Journal on Digital Signal Processing, 4(2), 8-16. https://doi.org/10.26634/jdp.4.2.5993

Abstract

References

Full Article (HTML)

Pdf

A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB

Manjinder Kaur* , Sangeet Pal Kaur**

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India. ** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Kaur,M., and Kaur,S,P. (2016). A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB. i-manager’s Journal on Digital Signal Processing, 4(2), 17-23. https://doi.org/10.26634/jdp.4.2.5994

Abstract

References

Full Article (HTML)

Pdf

Image Edge Preserving Filter with Impulse Noise Detection and Removal

Neelima* , Pankaj Mohindru**, Pooja Mohindru***

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India. **-*** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

Neelima., Mohindru,P., and Mohindru,P. (2016). Image Edge Preserving Filter with Impulse Noise Detection and Removal. i-manager’s Journal on Digital Signal Processing, 4(2), 24-33. https://doi.org/10.26634/jdp.4.2.5995

Abstract

References

Full Article (HTML)

Pdf

Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP

Anuja Mishra* , Sharad Mohan Shrivastava**

* PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India. ** Assistant Professor, Department of Electronics & Telecommunication, Shri Shankaracharya Technical Campus, Bhilai, India.

Mishra,A., and Shrivastava,S,M. (2016). Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP. i-manager’s Journal on Digital Signal Processing, 4(2), 34-42. https://doi.org/10.26634/jdp.4.2.5996

Abstract

References

Full Article (HTML)

Pdf

* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India.

** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Neelima* , Pankaj Mohindru, Pooja Mohindru*

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

-* Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

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

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