Browsing 08 Information and Computing Sciences by Author "Al-Ani, Ahmed"

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Browsing 08 Information and Computing Sciences by Author "Al-Ani, Ahmed"

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  • Al-Ani, Ahmed; Rabie, Alaleh; Van Dun, Bram; Dillon, Harvey (Springer Berlin Heidelberg, 2012)
    In this paper, we analyze the EEG rhythms of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. Investigation of the importance of the different EEG rhythms in terms of their capability in ...
  • Darvishi, Sam; Al-Ani, Ahmed (IEEE, 2007)
    The purpose of this paper is to analyze the electroencephalogram (EEG) signals of imaginary left and right hand movements, an application of Brain-Computer Interface (BCI). We propose here to use an Adaptive Neuron-Fuzzy ...
  • Khushaba, Rami; Al-Ani, Ahmed; Alsukker, Akram; Al-Jumaily, Adel Ali (Springer, 2008)
    Feature selection is an important step in many pattern recognition systems that aims to overcome the so-called curse of dimensionality problem. Although Ant Colony Optimization (ACO) proved to be a powerful technique in ...
  • Al-Ani, Ahmed (Pergamon-Elsevier Science Ltd, 2009)
    Feature selection has become an increasingly important field of research. It aims at finding optimal feature subsets that can achieve better generalization on unseen data. However, this can be a very challenging task, ...
  • Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (IEEE, 2008)
    In this paper, a novel feature selection algorithm based on differential evolution (DE) optimization technique is presented. The new algorithm, called DEFS, modifies the DE which is a real-valued optimizer, to suit the ...
  • Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (World Academy of Science, Engineering and Technology, 2009)
    One of the most important tasks in any pattern recognition system is to find an informative, yet small, subset of features with enhanced discriminatory power. In this paper, a new neuro-fuzzy discriminant analysis based ...
  • Alsukker, Akram; Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (IASTED, 2008)
    Feature selection is an indispensable pre-processing step when mining huge datasets that can significantly improve the overall system performance. This paper presents a novel feature selection method that utilizes both the ...
  • Alsukker, Akram; Al-Ani, Ahmed (IEEE Xplore, 2011)
    Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using ...
  • Alsukker, Akram; Khushaba, Rami; Al-Ani, Ahmed (IEEE, 2011)
    Genetic algorithm (GA) is one of the most widely used population-based evolutionary search algorithms. One of the challenging optimization problems in which GA has been extensively applied is feature selection. It aims at ...
  • Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (Springer, 2009)
    One of the fundamental motivations for feature selection is to overcome the curse of dimensionality. A novel feature selection algorithm is developed in this chapter based on a combination of Differential Evolution (DE) ...
  • Al-Ani, Ahmed; Alsukker, Akram; Khushaba, Rami (Elsevier, 2013)
    Differential evolution has started to attract a lot of attention as a powerful search method and has been successfully applied to a variety of applications including pattern recognition. One of the most important tasks in ...
  • Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (IEEE, 2008)
    The myoelectric signal (MES) from human muscles is usually utilized as an input to the controller of a multifunction prosthetic hand. In such a system, a pattern recognition approach is usually employed to discriminate ...
  • Khushaba, Rami; Alsukker, Akram; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (IEEE, 2008)
    n this paper, a new feature extraction method utilizing ant colony optimization in the selection of wavelet packet transform (WPT) best basis is presented and adopted in classifying biomedical signals. The new algorithm, ...
  • Alsukker, Akram; Al-Ani, Ahmed; Atiya, Amir (INSTICC - Institute for Systems and Technologies of Information, Control and Communication, 2009)
    We present in this paper a simple, yet valuable improvement to the traditional k-Nearest Neighbor (kNN) classifier. It aims at addressing the issue of unbalanced classes by maximizing the class-wise classification accuracy. ...
  • Al-Ani, Ahmed; Talaat, Amira; Atiya, Amir; Mokhtar, Sahar; Fayek, Magda (Springer Berlin Heidelberg, 2012)
    Penalized likelihood is a general approach whereby an objective function is defined, consisting of the log likelihood of the data minus some term penalizing non-smooth solutions. Subsequently, this objective function is ...
  • Al-Ani, Ahmed; Deriche, Mohamed; Chebil, Jalel (IOS Press, 2003)
    In this paper, we discuss the problem of feature selection and the importance of using mutual information in evaluating the discrimination ability of feature subsets between class labels. Because of the difficulties ...
  • Khushaba, Rami; Alsukker, Akram; Al-Ani, Ahmed; Zomaya, Albert; Al-Jumaily, Adel Ali (IOS Press, 2009)
    Accurate and computationally efficient myoelectric control strategies have been the focus of a great deal of research in recent years. Although many attempts exist in literature to develop such strategies, deficiencies ...
  • Alsukker, Akram; Khushaba, Rami; Al-Ani, Ahmed (IEEE, 2010)
    Traditional k-NN classifier poses many limitations including that it does not take into account each class distribution, importance of each feature, contribution ofeach neighbor, and the number ofinstances for each class. ...
  • Khushaba, Rami; Al-Ani, Ahmed; Al-Jumaily, Adel Ali (IEEE, 2010)
    Developing accurate and powerful electromyogram (EMG) driven prostheses controllers that can provide the amputees with effective control on their artificial limbs, has been the focus of a great deal of research in the past ...
  • Khushaba, Rami; Elliott, Rosalind; Alsukker, Akram; Al-Ani, Ahmed; Mckinley, Sharon (IEEE, 2010)
    Sleep-stage scoring plays an important role in analyzing the sleep patterns of people. Studies have revealed that Intensive Care Unit (ICU) patients do not usually get enough quality sleep, and hence, analyzing their sleep ...