Volume 18 (2024)
Volume 17 (2023)
Volume 16 (2022)
Volume 15 (2021)
Volume 14 (2020)
Volume 13 (2019)
Volume 12 (2018)
Volume 11 (2017)
Volume 10 (2016)
Volume 9 (2015)
Volume 8 (2014)
Volume 7 (2013)
Volume 6 (2012)
Volume 5 (2011)
Volume 4 (2010)
Volume 3 (2009)
Volume 1 (2007)
Detection of Acute Atrial-Ventricular Arrhythmias Based on ECG Delineator: Evaluation on MIT/BIH Standard Databases
Volume 2, Issue 1 , June 2008, Pages 1-10

https://doi.org/10.1234/mjee.v2i1.3

Abstract
  AbstractIn this paper we use an efficient arrhythmia algorithm based on wavelet transform. In first step, QRS complexes are detected. Then each QRS is delineated by detecting and identifying the peaks of the individual waves, complex onset and end. Then the determination of P and T wave peaks, onset ...  Read More

A Study on Structure, Performance, Fabrication and Application of Micro Motors
Volume 2, Issue 1 , June 2008, Pages 11-25

https://doi.org/10.1234/mjee.v2i1.38

Abstract
  Nowadays, micro motors have widespread applications in the industry. However, not many references exist about these motors. To remove this problem, a comprehensive review on micro motors is presented in this paper. For this purpose, different type of micro motors discussed and their potential and challenges ...  Read More

CSM Temper Mill System Identification and Modeling of Mobarake Steel Complex
Volume 2, Issue 1 , June 2008, Pages 27-35

https://doi.org/10.1234/mjee.v2i1.39

Abstract
  System identification is defined as modeling a system, using the input-output data. In this paper, CSM temper mill line was studied and parametric system identification was explained. Using ARX method, the experimental system was modeled and identified. Good agreement was obtained when comparing extracted ...  Read More

A New Hybrid Watermarking Algorithm for Images in Frequency Domain
Volume 2, Issue 1 , June 2008, Pages 37-49

https://doi.org/10.1234/mjee.v2i1.40

Abstract
  In recent years, digital watermarking has become a popular technique for digital images by hiding secret information which can protect the copyright. The goal of this paper is to develop a hybrid watermarking algorithm. This algorithm used DCT coefficient and DWT coefficient to embedding watermark, and ...  Read More

EEG Pattern Recognition to Diagnose Epilepsy Using Wavelet and Chaos Transformations
Volume 2, Issue 1 , June 2008, Pages 51-59

https://doi.org/10.1234/mjee.v2i1.41

Abstract
  By the time-frequency transformations like wavelet and chaos theory to find the feature from sub-bands, it is possible to diagnose the epilepsy although there are some noises and signals. To decompose the EEG into sub-bands such as delta, theta, alpha, beta and gamma, wavelet analysis is used. Chaos ...  Read More

Synthesis of a Logic-Based Switching H2/H∞ Controller:A Fuzzy Supervisor Approach
Volume 2, Issue 1 , June 2008, Pages 61-69

https://doi.org/10.1234/mjee.v2i1.42

Abstract
  In this paper, the synthesis of switching H2/H∞ controller is considered which achieves a minimum bound on the H2 performance level, while satisfying the H∞ performance. The proposed hybrid control scheme is based on a fuzzy supervisor which manages the combination of controllers. A convex formulation ...  Read More

Networked Control System Simulation Methods:A Comparative Study
Volume 2, Issue 1 , June 2008, Pages 71-82

https://doi.org/10.1234/mjee.v2i1.44

Abstract
  In this paper, we examine several frameworks for NCS simulation: a MATLAB-based package called True Time, the Agent/Plant addition to the ns-2 network simulator, and other MATLAB -based frameworks. We analyze the accuracy, speed, and ease of use of two different methods of simulating system dynamics ...  Read More

Automotic Recognition of Sleep Spindles Based on Two-Stage Classifier with Artificial Neural Networks and Support Vector Machines
Volume 2, Issue 1 , June 2008, Pages 83-90

https://doi.org/10.1234/mjee.v2i1.45

Abstract
  Sleep spindles are one of the most important transient waveforms found in the sleep EEG signal. Here, we introduce a two-stage procedure based on artificial neural networks for the automatic recognition of sleep spindles (SS) in a 19-channel electroencephalographic signal. In the first stage, a pre-processing ...  Read More