International Journal of Electrical and Computer Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Articles
6,301 Documents
An Effective Noise Adaptive Median Filter for Removing High Density Impulse Noises in Color Images
S. Abdul Saleem;
T. Abdul Razak
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i2.pp611-620
Images are normally degraded by some form of impulse noises during the acquisition, transmission and storage in the physical media. Most of the real time applications usually require bright and clear images, hence distorted or degraded images need to be processed to enhance easy identification of image details and further works on the image. In this paper we have analyzed and tested the number of existing median filtering algorithms and their limitations. As a result we have proposed a new effective noise adaptive median filtering algorithm, which removes the impulse noises in the color images while preserving the image details and enhancing the image quality. The proposed method is a spatial domain approach and uses the 3×3 overlapping window to filter the signal based on the correct selection of neighborhood values to obtain the effective median per window. The performance of the proposed effective median filter has been evaluated using MATLAB, simulations on a both gray scale and color images that have been subjected to high density of corruption up to 90% with impulse noises. The results expose the effectiveness of our proposed algorithm when compared with the quantitative image metrics such as PSNR, MSE, RMSE, IEF, Time and SSIM of existing standard and adaptive median filtering algorithms.
Investigation and Analysis of Space Vector Modulation with Matrix Converter Determined Based on Fuzzy C-Means Tuned Modulation Indexs
Ch. Amarendra;
K. Harinadh Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i5.pp1939-1947
Matrix converter performs energy conversion by directly connecting input phases with output phases through bidirectional switches. Conventional power converters make use of bulky reactive elements which are subjected to ageing, reduce the system reliability. The matrix converter (MC) stands as an alternative to conventional power converter. Furthermore MC’s provide bidirectional power flow nearly sinusoidal input and sinusoidal output waveform and controllable input power factor. In this work, three modulation methods have been simulated using MATLAB and compared on the basis of input current harmonics, output voltage harmonics and number of switching per cycle. The three techniques simulated are, Optimal Venturini method, Direct Space Vector Modulation (DSVM) and Indirect Space Vector Modulation (ISVM) on Conventional Matrix Converter (CMC) and obtained form Fuzzy c-Means (FCM). DSVM with FCM is proposed for obtainting best results compared to other three techniques.
Performance Comparison between Classic and Intelligent Methods for Position Control of DC Motor
Navid Moshtaghi Yazdani;
Arezoo Yazdani Seqerloo
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 3: June 2014
Publisher : Institute of Advanced Engineering and Science
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Controlling DC motors is mainly done by controlling either voltage or field of their armature. Numerous methods have been proposed so far for this purpose. Some intelligent methods such as XCSR and machine learning systems are used to control position of a separately excited DC motor. Having set output position of the motor to its basic position, voltage of armature becomes zero and the motor stops working. Characteristic features of the methods in this paper are resistance against changing friction and moment of inertia. Meanwhile, time to reach stability in this type of controllers is considerably lower than that of PID controller with no oscillations being observed in the responses.DOI:http://dx.doi.org/10.11591/ijece.v4i3.5355
Solving output control problems using Lyapunov gradient-velocity vector function
М. А. Beisenbi;
Zh. O Basheyeva
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i4.pp2874-2879
This paper describes a controller and observer parameter definition approach in one input-one output (closed-loop) control systems using Lyapunov gradient-velocity vector function. Construction of the vector function is based on the gradient nature of the control systems and the parity of the vector functions with the potential function from the theory of catastrophe. Investigation of the closed-loop control system’s stability and solution of the problem of controller (determining the coefficient of magnitude matrix) and observer (calculation of the matrix elements of the observing equipment) synthesis is based on the direct methods of Lyapunov. The approach allows to select parameters based on the requested characteristics of the system.
Development of a Condition Monitoring Algorithm for Industrial Robots based on Artificial Intelligence and Signal Processing Techniques
Alaa Adulhady Jaber;
Robert Bicker
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i2.pp996-1009
Signal processing plays a significant role in building any condition monitoring system. Many types of signals can be used for condition monitoring of machines, such as vibration signals, as in this research; and processing these signals in an appropriate way is crucial in extracting the most salient features related to different fault types. A number of signal processing techniques can fulfil this purpose, and the nature of the captured signal is a significant factor in the selection of the appropriate technique. This chapter starts with a discussion of the proposed robot condition monitoring algorithm. Then, a consideration of the signal processing techniques which can be applied in condition monitoring is carried out to identify their advantages and disadvantages, from which the time-domain and discrete wavelet transform signal analysis are selected.
A Context-based Numeral Reading Technique for Text to Speech Systems
Soumya Priyadarsini Panda;
Ajit Kumar Nayak
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i6.pp4533-4544
This paper presents a novel technique for context based numeral reading in Indian language text to speech systems. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. For this purpose, the three Indian languages Odia, Hindi and Bengali are considered. To analyze the performance of the proposed technique, a set of experiments are performed considering different context of numeral pronunciations and the results are compared with existing syllable-based technique. The results obtained from different experiments shows the effectiveness of the proposed technique in producing intelligible speech out of the entered text utterances compared to the existing technique even with very less storage and execution time.
A Three-Point Directional Search Block Matching Algorithm
A.V. Paramkusam;
D. Laxma Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i1.pp230-237
This paper proposes compact directional asymmetric search patterns, which we have named as three-point directional search (TDS). In most fast search motion estimation algorithms, a symmetric search pattern is usually set at the minimum block distortion point at each step of the search. The design of the symmetrical pattern in these algorithms relies primarily on the assumption that the direction of convergence is equally alike in each direction with respect to the search center. Therefore, the monotonic property of real-world video sequences is not properly used by these algorithms. The strategy of TDS is to keep searching for the minimum block distortion point in the most probable directions, unlike the previous fast search motion estimation algorithms where all the directions are checked. Therefore, the proposed method significantly reduces the number of search points for locating a motion vector. Compared to conventional fast algorithms, the proposed method has the fastest search speed and most satisfactory PSNR values for all test sequences.
Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors
Hayder Yousif Abed;
Abdulrahim Thiab Humod;
Amjad J. Humaidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i1.pp265-274
This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.
Towards an Optimal Speaker Modeling in Speaker Verification Systems using Personalized Background Models
Ayoub Bouziane;
Jamal Kharroubi;
Arsalane Zarghili
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i6.pp3655-3663
This paper presents a novel speaker modeling approachfor speaker recognition systems. The basic idea of this approach consists of deriving the target speaker model from a personalized background model, composed only of the UBM Gaussian components which are really present in the speech of the target speaker. The motivation behind the derivation of speakers’ models from personalized background models is to exploit the observeddifference insome acoustic-classes between speakers, in order to improve the performance of speaker recognition systems.The proposed approach was evaluatedfor speaker verification task using various amounts of training and testing speech data. The experimental results showed that the proposed approach is efficientin termsof both verification performance and computational cost during the testing phase of the system, compared to the traditional UBM based speaker recognition systems.
Measuring information credibility in social media using combination of user profile and message content dimensions
Erwin B. Setiawan;
Dwi H. Widyantoro;
Kridanto Surendro
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i4.pp3537-3549
Information credibility in social media is becoming the most important part of information sharing in the society. The literatures have shown that there is no labeling information credibility based on user competencies and their posted topics. This study increases the information credibility by adding new 17 features for Twitter and 49 features for Facebook. In the first step, we perform a labeling process based on user competencies and their posted topic to classify the users into two groups, credible and not credible users, regarding their posted topics. These approaches are evaluated over ten thousand samples of real-field data obtained from Twitter and Facebook networks using classification of Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (Logit) and J48 algorithm (J48). With the proposed new features, the credibility of information provided in social media is increasing significantly indicated by better accuracy compared to the existing technique for all classifiers.