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67 results for “Perceptron”
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Research ArticleOpen accessIn the abstractAn Improved Approach for Detecting Car in Video using Neural Network ModelS. N. Sivanandam, T. Senthil KumarThe study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no system has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a … …Journal of Computer Science, Vol. 8, Issue 10 · 1 Sep 2012 · 7,151 accessesView PDFCite
Research ArticleOpen accessIn the abstractAccurate Wavelet Neural Network for Efficient Controlling of an Active Magnetic Bearing SystemYoussef Harkouss, Souhad Mcheik, Roger AchkarProblem statement: The synthesis of a command by the neural network has an excellent advantage over the classical one such as PID. This study presented a fast and accurate Wavelet Neural Network (WNN) approach for efficient controlling of an Active Magnetic Bearing (AMB) system. Approach: The proposed approach combined neural network with the wavelet theory. Wavelet theory may be exploited … …Journal of Computer Science, Vol. 6, Issue 12 · 9 Nov 2010 · 15,569 accessesView PDFCite
Research ArticleOpen accessIn the abstractDWT to Classify Automatically the Placental Tissues Development: Neural Network ApproachMohammad Ayache, Mohamad Khalil, Francois TranquartProblem statement: This study proposed an approach for classification of placental tissues development using ultrasound images. Approach: This approach was based to the selection of tissues, feature extraction by discrete wavelet transform and classification by neural network and especially the Multi Layer Perceptron (MLP). Results: The proposed approach was tested for ultrasound placental images; resulting in 95% success rate. Conclusion/Recommendations: … …Journal of Computer Science, Vol. 6, Issue 6 · 30 Jun 2010 · 6,997 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting the Severity of Breast Masses with Ensemble of Bayesian ClassifiersAlaa M. ElsayadProblem statement: This study evaluated two different Bayesian classifiers; tree augmented Naive Bayes and Markov blanket estimation networks in order to build an ensemble model for prediction the severity of breast masses. The objective of the proposed algorithm was to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,299 accessesView PDFCite
Research ArticleOpen accessIn the abstractKnowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion SolutionsWan Fazlida Hanim Abdullah, Mohd Alaudin Mohd Ali, Md Shabiul Islam, Masuri OthmanProblem statement: The Ion-Sensitive Field-Effect Transistor (ISFET) is a metal-oxide field-effect transistor-based sensor that reacts to ionic activity at the electrolye/membrane/gate interface. The ionic sensor faces issue of selectivity from interfering ions that contribute to the sensor electrical response in mixed solutions. Approach: We present the training data collection of ISFET voltage response for the purpose of post-processing stage neural … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,816 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimal Thyristor Control Series Capacitor Neuro-Controller for Damping OscillationsM. Magaji, M. W. MustafaThis study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive "pseudo-linear regression". Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,565 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Statistical Speech Segmentation Using Connectionist ApproachM. S. Salam, Dzulkifli Mohamad, S. H. SallehProblem statement: Speech segmentation is an important part for speech recognition, synthesizing and coding. Statistical based approach detects segmentation points via computing spectral distortion of the signal without prior knowledge of the acoustic information proved to be able to give good match, less omission but lot of insertion. These insertion points dropped segmentation accuracy. Approach: This study proposed a fusion … …Journal of Computer Science, Vol. 5, Issue 4 · 30 Apr 2009 · 7,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Network Approach in Radar Target ClassificationN.K. Ibrahim, R.S.A. Raja Abdullah, M.I. SaripanProblem statement: This study unveils the potential and utilization of Neural Network (NN) in radar applications for target classification. The radar system under test is a special of it kinds and known as Forward Scattering Radar (FSR). In this study the target is a ground vehicle which is represented by typical public road transport. The features from raw radar signal … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 9,370 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Hidden Layer Neurons on the Classification of Optical Character Recognition Typed Arabic NumeralsNidal F. Shilbayeh, Mahmoud Z. IskandaraniProblem statement: The effect of varying the number of nodes in the hidden layer and number of iterations are important factors in the recognition rate. In this paper, a novel and effective criterion based on Cross Pruning (CP) algorithm is proposed to optimize number of hidden neurons and number of iterations in Multi Layer Perceptron (MLP) neural based recognition system. … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,556 accessesView PDFCite