Ikhlas Mahmoud Farhan
University of Technology

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A nonlinearities inverse distance weighting spatial interpolation approach applied to the surface electromyography signal Ayad Assad Ibrahim; Ikhlas Mahmoud Farhan; Mohammed Ehasn Safi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1530-1539

Abstract

Spatial interpolation of a surface electromyography (sEMG) signal from a set of signals recorded from a multi-electrode array is a challenge in biomedical signal processing. Consequently, it could be useful to increase the electrodes' density in detecting the skeletal muscles' motor units under detection's vacancy. This paper used two types of spatial interpolation methods for estimation: Inverse distance weighted (IDW) and Kriging. Furthermore, a new technique is proposed using a modified nonlinearity formula based on IDW. A set of EMG signals recorded from the noninvasive multi-electrode grid from different types of subjects, sex, age, and type of muscles have been studied when muscles are under regular tension activity. A goodness of fit measure (R2) is used to evaluate the proposed technique. The interpolated signals are compared with the actual signals; the Goodness of fit measure's value is almost 99%, with a processing time of 100msec. The resulting technique is shown to be of high accuracy and matching of spatial interpolated signals to actual signals compared with IDW and Kriging techniques.
Enhancement of code division multiple access system performance using raptor codes Ikhlas Mahmoud Farhan; Dhafer R. Zaghar; Hadeel Nasrat Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1460-1468

Abstract

Some kinds of communication systems work in very low signal-to-noise (LSNR) environments. For these systems to function reliably, specific techniques and methodologies have to be used to mitigate the degrading effects of the channel. The channel coding method is the key element in most LSNR communication systems, but emphasizing the code division multiple access (CDMA) is a new transmission technique in these channels. To enhance the CDMA scheme's system capacity and reach unprecedented ranges of LSNR values in wireless sensor network. This paper suggests combining CDMA with certain types of channel coding algorithms, such as the raptor codes. The raptor channel encoding technique has improved the CDMA system's performance when using binary phase-shift keying (BPSK) modulation in additive white gaussian noise (AWGN) channels. It has achieved a low bit error rate in range of 10-7 at Eb/No value of (-3) dB and about 10-6 at shannon's limit. The Raptor-coded CDMA scheme works well for channel signal to noise ration (SNR) values of greater than -9 dB, showing an improvement of about 7 dB compared with turbo/convolutional channel coding methods used with the CDMA system bit error rate (BER) and throughput. On the other hand, it has been shown that the convolutional encoder presents the weakest performance compared to both the turbo and raptor codes.