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American Journal of Signal Processing
Number of Followers: 14  Open Access journalISSN (Print) 2165-9354 - ISSN (Online) 2165-9362 Published by SAP  [105 journals]
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- Mitigation of Continuous Wave Narrow-Band Interference in QPSK
Demodulation Using Adaptive IIR Notch Filter
Abstract: Publication year: 2020Source: American Journal of Signal Processing, Volume 10, Number 1Abdelrahman El Gebali, René Jr LandryA Continuous Wave Narrow-Band Interference (CW-NBI) can reduce the effective signal-to-noise ratio (SNR), and the quality of the Signals-of-Interest (SoI) in any wireless transmission such as in a Digital Video Broadcasting (DVB-S2) receiver. Therefore, this paper proposes a novel low-complexity anti-jamming filter to mitigate unknown CW-NBI. The approach is to develop a robust least-mean-squared (LMS) algorithm for mitigating CW-NBI in QPSK demodulation but could be used in any communication system. The proposed filter is based on two open-loop Adaptive lattice Notch Filter (ALNF) structure and an LMS algorithm. Each ALNF is composed of a second-order Infinite-Impulse-Response (IIR) filter. The first ALNF is used to estimate the Jamming to Signal Ratio (JSR) and the frequency of the interference. In contrast, the second ALNF is used to remove the interference and adjust the depth of the notch according to the estimated JSR. On the other hand, the LMS algorithm is used to obtain and then track the interference. Simulation results show the performance of the proposed IIR notch filter with the LMS algorithm in reducing and mitigating interference. Also, it provides better output SNR of the notch filter for a given value of JSR and BER performance. For example, at the JSR value of -6 dB, the SNR output of the proposed IIR notch filter was enhanced by 9 dB compared to the case without a filter when
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- An Exact Pseudo-Static Time-Domain Theory of Natural Pulse Width
Modulation
Abstract: Publication year: 2020Source: American Journal of Signal Processing, Volume 10, Number 1Dante C. Youla, Fred WinterOwing in part to the increasing importance of pulse width modulation (PWM) as an alternative analog communication technique for optical data links there has been a resurgence of interest in both new and traditional methods of analysis. Of the latter, the old pseudo-static approach is undoubtedly the simplest, although long considered by many to be only an approximation. One principal object of this paper is to prove that pseudo-static analysis is exact and explicit for natural ramp-intersective PWM and allows easy derivation of all pertinent time-domain formulas. As shown in detail by example, it then may be possible to carry out spectral and modulation-demodulation analysis in a straightforward physically insightful quantitative manner.
- Analysis of Empirical Mode Decomposition Method of Heart Rate Extraction
from Motion Artifact Corrupted PPG Signal
Abstract: Publication year: 2019Source: American Journal of Signal Processing, Volume 9, Number 1A. H. M. Zadidul Karim, Muhammad Towhidur Rahman, Md. Abdullah Al Mahmud, Shikder Shafiul Bashar, Md. Sazal Miah, Maliha MariumThe main objective of this paper is to detect the heart rate from any wearable wrist device. The number of times one’s heart beats per minute is called heart rate. Theoretically, any body part can be used to measure heart rate through the sensor of the device, although wrist type things are commonly targeted. In this paper the heart rate monitoring is based on photoplethysmoghaphy (PPG). But during the physical exercise it is tough to get the heart rate (HR) because then the PPG signals are vulnerable to motion artifacts (MA). To find HR an algorithm is presented here, which combines ensemble empirical mode decomposition (EEMD) with spectrum subtraction (SS). Ensemble Empirical Mode Decomposition decomposes a PPG signal and acceleration signal into intrinsic mode function (IMF). That’s mean it jointly estimates the spectra of PPG signals and simultaneous acceleration signals, utilizing the multiple measurement vector model in sparse signal recovery. This method can easily identify and remove the spectral peaks of motion artifact (MA) from the PPG spectra. The method explained in this paper has better performance than other methods.
- Derivation of Euler's Formula and ζ(2k) Using the Nyquist-Shannon
Sampling Theorem
Abstract: Publication year: 2019Source: American Journal of Signal Processing, Volume 9, Number 1Er'el GranotThere are multiply approaches to prove Euler's well-known formula, however, none of them is trivial or simple. In this paper we utilize Nyquist-Shannon sampling theorem to prove Euler's formula in particular and Riemann's
in general in a straightforward approach. The presented method allows calculating the summation of several other similar series, such as 
, and even more surprising ones such as 
.
- Study of Early Age Behaviour of Mortar Pastes with Different Dosages of
Alkaline Accelerator for Shotcrete: The Use of the Ultrasound Pulse Echo
Method
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 2Nabil Khatib, El Houssaine Ouacha, Bouazza Faiz, Mohamed Ezzaidi, Hicham BanouniConcrete produced today is usually mixed with either chemical additions to the cement, chemical admixtures in the concrete, or both. Thus, the change of properties of cementitious concrete, mainly the rheology and the setting and the hardening, is strongly dependent on the admixtures used. Alkali-accelerating admixtures used in shotcrete, alter a number of properties of the cementitious system, including its resistivity and early hardening behaviour. The main focus of this research was to investigate the possible use of ultrasound pulse echo method, using P-waves, to evaluate the influence of an alkali-accelerating admixture for shotcrete on mortar behaviour at early age. The sensitivity to alkaline accelerator and its dosage were evaluated. The tested mortar mixes contained Portland composite cement CPJ 45. The presence of alkali-accelerating admixture in the mortar mixes and its dosage, influence the evolution of the modulus of the reflection coefficient and the peak-to-peak amplitude of reflected echoes, during the early time of the hardening period. Also, the alkaline accelerator caused a significant reduction in young modulus at early ages, and this for all dosage tested.
- Monitoring System for Power Transformer Windings Hot Spot Temperature
Using Fiber Optic Sensors, Kalman Filter and Integration in SCADA System
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 2Marcel Nicola, Claudiu-Ionel Nicola, Dumitru Sacerdoțianu, Iulian Hurezeanu, Marian DuțăThis article presents the implementation based on LabVIEW of a monitoring system using fiber optic sensors for the measurement of hot spot temperature of the transformer windings, which employs a Kalman filter to reduce the measurement noise, and is integrated into a SCADA (Supervisory Control and Data Acquisition) system. The system shows the online evolution of temperatures, automatically creates and prints reports, stores the acquired data as TDMS (Technical data Management Streaming) type files and in a MySQL Server type database. For the connection between the monitoring system and the SCADA a new OPC UA (OLE Object linking and embedding for Process Control Unified Architecture) is used, which simplifies the function collaboration and enterprise deployment. The developed monitoring system implements a unit to access and transmit real time data over the Intranet or Internet, using JSON (JavaScript Object Notation) for the communication between the integrated Web Server and the Web Browser, provides warning reports and sends an e-mail to default addresses. The monitoring of the acquired data, the system operation and SCADA integration of the system presented have been tested using both synthesized virtual signals and real signals. The presented system could be used for monitoring and SCADA integration of the power transformer windings hot spot temperature in the electric power transmission network.
- Electronic Health Care Monitoring System (EHCMS)
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 2Musab Nur-Elhuda Mohammed, Faisal Mohammed Abd-AllahWe have developed offline & a real-time algorithms for detection of Q,R,S wave of ECG & PPG signals, monitoring patient continousley by doctor and rapidly increase of patient full health care (EHCMS) and suggest precautions to the patient before entering critical case, and classification of some disease that is faced patient depend on vital signs that is capturing from patient like bradycardia and tachycardia by analysis of Q,R,S wave, this work is part of M.I.C.U.
- A Fast Fractional-Pixel Search Algorithm Based on Linear-Prediction Motion
Estimation
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 1Lung-Jen Wang, Wen-Ming TaiThe fractional-pixel motion estimation is used accurately for motion vector prediction in the H.264/AVC video coding. Based on the linear prediction and a small diamond search algorithm, a fast fractional-pixel search algorithm is proposed in this paper. The proposed method substantially solves the complexity of the calculation of the fractional-pixel motion estimation needed in the H.264/AVC video coding if the image resolution is increased. Finally, experimental results show that the proposed algorithm is superior in performance and reduces around 60% computations for the fractional-pixel calculations.
- Optimization of Transformation Matrix for 3D Cloud Mapping Using Sensor
Fusion
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 1Hai T. Nguyen, Viet B. Ngo, Hai T. QuachThis paper proposes an optimization method of transformation matrix for 3D cloud mapping for indoor mobile platform localization using fusion of a Kinect camera system and encoder sensors. In this research, RGB and depth images obtained from the Kinect system and encoder data are calculated to produce transformation matrices. A Kalman filter algorithm is applied to optimize these matrices and then produce a transformation matrix which minimizes cumulative error for building 3D cloud mapping. For mobile platform localization in an indoor environment, a SIFT algorithm is employed for feature detector and descriptor to determine similar points of two consecutive image frames for RGB-D transformation matrix. In addition, another transformation matrix is reconstructed from encoder data and it is combined with the RGB-D transformation matrix to produce the optimized transformation matrix using Kalman filter. This matrix allows to minimize cumulative error in building 3D point cloud image for robotic localization. Experimental results with mobile platform in door environment will show to illustrate the effectiveness of the proposed method.
- Performance Evaluation of Various Hyperspectral Nonlinear Unmixing
Algorithms
Abstract: Publication year: 2018Source: American Journal of Signal Processing, Volume 8, Number 1Awabed Jibreen, Nourah Alqahtani, Ouiem BchirNonlinear unmixing of hyperspectral images has shown considerable attention in image and signal processing research areas. Hyperspectral unmixing identifies endmembers spectral signatures and the abundance fractions of each endmemeber within each pixel of an observed hyperspectral scene. Over the last few years, several nonlinear unmixing algorithms have been proposed. This paper presents an empirical comparison of several popular and recent algorithms of supervised nonlinear unmixing algorithms. Namely, we compared Kernel-based algorithms, graph Laplacian regularization algorithm, and nonlinear unmixing algorithm using a generalized bilinear model (GBM). These unmixing algorithms estimate the abundances of linear, bilinear and intimate mixtures of hyperspectral data. We assessed the performance of these algorithms using Root Mean SquareError on the same data sets.
