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(searched for: doi:10.1109/act.2010.11)
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, Monika Mittal
Journal of The Institution of Engineers (India): Series B, Volume 100, pp 489-497; https://doi.org/10.1007/s40031-019-00398-9

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Published: 4 December 2018
BioMedical Engineering OnLine, Volume 17, pp 1-23; https://doi.org/10.1186/s12938-018-0613-2

Abstract:
The study presents a recursive least-squares estimation method with an exponential forgetting factor for noise removal in functional near-infrared spectroscopy data and extraction of hemodynamic responses (HRs) from the measured data. The HR is modeled as a linear regression form in which the expected HR, the first and second derivatives of the expected HR, a short-separation measurement data, three physiological noises, and the baseline drift are included as components in the regression vector. The proposed method is applied to left-motor-cortex experiments on the right thumb and little finger movements in five healthy male participants. The algorithm is evaluated with respect to its performance improvement in terms of contrast-to-noise ratio in comparison with Kalman filter, low-pass filtering, and independent component method. The experimental results show that the proposed model achieves reductions of 77% and 99% in terms of the number of channels exhibiting higher contrast-to-noise ratios in oxy-hemoglobin and deoxy-hemoglobin, respectively. The approach is robust in obtaining consistent HR data. The proposed method is applied for both offline and online noise removal.
, Sencer Öztüfekçi, Ismail Kavdır
Journal of Food Measurement and Characterization, Volume 12, pp 2819-2834; https://doi.org/10.1007/s11694-018-9897-y

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Varun Gupta, Monika Mittal
2016 International Conference on Electrical Power and Energy Systems (ICEPES) pp 221-225; https://doi.org/10.1109/icepes.2016.7915934

Abstract:
Sinus patients, both humans and animals, are increasing day by day in the world. That's why today signal analysis has been the need to know the diseases in the patient. Biomedical signal processing (BSP) has great importance in the life of every human and animal. Without BSP signals cannot be analysed, resulting in failure of disease acknowledgment. In this paper respiratory signals of Sinus and Normal Person has been analysed using Principal Component Analysis (PCA), Fast Fourier Transform (FFT) and Auto-Regressive Time-Frequency Analysis (ARTFA). PCA is used where dimension reduction is required. It has found many applications in BSP. ARTFA allows us to follow the changes in frequencies involved in the signal through time. For this, frequency changes in time are required to be observed. FFT examines the signal in frequency domain and calculates the spectral function (SF). In this paper, the variance of First Principal Component and Second Principal Component have been calculated for Sinus and Normal Person and these values are 86.94%, 13.05% and 92.733%, 7.266% respectively.
Chang Liu, Xiao Cen Li
Advanced Materials Research, Volume 787, pp 508-512; https://doi.org/10.4028/www.scientific.net/amr.787.508

Abstract:
Fourier transform phase angle carries shape information of image, statistics phase angles of all pixels will reflect the image shape characteristics. According to this theory, for study the relationship between image texture and papermaking method, a novel method for description linear image texture was proposed, and experiments were carried out. The experiments showed that the new method achieved texture feature extraction, suitable for handmade paper microscopic image analysis.
Gavendra Singh, Varun Gupta, Shekhar Pundir, Shobhit Sharma
Advanced Materials Research, Volume 403-408, pp 114-119; https://doi.org/10.4028/www.scientific.net/amr.403-408.114

Abstract:
Many authors have been found the difference between Fourier Transform & Laplace Transform. In this paper we are highlighting the major or you can say interesting difference between Fourier Transform & Laplace Transform . If we look on the step signal , we will found that there will be interesting difference among these two transforms. In this paper we are giving the interesting reason behind this.
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