Marzuki Khalid

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Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial(More)
This paper investigates the intrinsic ability of Gabor representation and support vector machines (SVM) in capturing discriminatory content for face verification task. The idea is to decompose a face image into different spatial frequencies (scales) and orientations where salient discriminant features may appear. Dimensionality reduction is adopted to(More)
Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capability. However, NN does not guarantee good generalization due to Empirical Risk minimization (ERM) principle that it uses. In our work, we focus on using the support vector machine(More)
Fuzzy logic, neural networks and genetic algorithms are three popular artificial intelligence techniques that are widely used in many applications. Due to their distinct properties and advantages, they are currently being investigated and integrated to form new models or strategies in the areas of system control. In this paper, a neuro-fuzzy controller(More)
-Fuzzy ARTMAP is one of the recently proposed neural network paradigm where the fuzzy logic is incorporated. In this paper, we compare the Fuzzy ARTMAP neural network and the well-known back-propagation based Multi-layer perceptron (MLP), in the context of hand-written character recognition problem. The results presented in this paper shows that the Fuzzy(More)
This paper describes an approach to combine neural network (NN) and Hidden Markov models (HMM) for solving handwritten word recognition problem. The preprocessing involves generating a segmentation graph that describes all possible ways to segment a word into letters. To recognize a word, the NN computes the observation probabilities for each letter(More)
-This paper describes an offline cursive handwritten word recognition system that combines Hidden Markov Models (HMM) and Neural Networks (NN). Using a fast left-right slicing method, we generate a segmentation graph that describes all possible ways to segment a word into letters. The NN computes the observation probabilities for each letter hypothesis in(More)
Deoxyribonucleic Acid or DNA computing has emerged as an interdisciplinary field that draws together chemistry, molecular biology, computer science, and mathematics. From the DNA computing point of view, it has been proven that it is possible to solve weighted graph problems by exploiting some characteristics of DNA such as length, concentration, and(More)