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139 results for “Training Algorithm”

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Research ArticleOpen accessIn the abstractArtificial Neural Network Based Rotor Capacitive Reactance Control for Energy Efficient Wound Rotor Induction MotorK. Ranjith Kumar, S. Palaniswami, K. Siva KumarProblem statement: The Rotor reactance control by inclusion of external capacitance in the rotor circuit has been in recent research for improving the performances of Wound Rotor Induction Motor (WRIM). The rotor capacitive reactance is adjusted such that for any desired load torque the efficiency of the WRIM is maximized. The rotor external capacitance can be controlled using a dynamic … …Journal of Computer Science, Vol. 8, Issue 7 · 26 May 2012 · 7,162 accessesView PDFCite
Research ArticleOpen accessIn the abstractPalmprint Recognition using Feature Level FusionR. Gayathri, P. RamamoorthyProblem statement: Palmprint based biometric method has gained high impact over the other biometric methods due to its ease of acquisition, reliability and high client acceptance. Multiple feature extraction from image gives higher accuracy of the authentication system. Approach: This study presents the palmprint based identification methodology which uses the Gabor wavelet entropy to extract multiple features existing on the … …Journal of Computer Science, Vol. 8, Issue 7 · 19 May 2012 · 6,982 accessesView PDFCite
Research ArticleOpen accessIn the abstractSymbol Timing Estimation in Multiband Orthogonal Frequency Division Multiplexing based Ultrawide band SystemM. N. Suresh, S. J. Thiruvengadam, V. AbhaikumarProblem statement: The Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) Based Ultra Wideband system (UWB) is highly susceptible to symbol timing error. Symbol timing estimation in MB-OFDM based UWB is difficult due to the presence of strongest path at delayed instant. Approach: Symbol timing estimation has two steps namely a coarse estimation and a fine estimation. In this study, a maximum … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 10 Feb 2012 · 7,101 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,199 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of Pecan Weevils through Image ProcessingS.M. Al-Saqer, P. Weckler, J. Solie et al.Abstract: Problem Statement: Pecan weevil is one of the most destructive pests of Oklahoma. The scope of this study is to develop a recognition system that can serve in a wireless imaging network for monitoring pecan weevils. Approach: The recognition methods used in this study are based on template matching. Five recognition methods were implemented: Normalized cross-correlation, Fourier descriptors, Zernike … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 1 · 15 Dec 2010 · 8,775 accessesView PDFCite
Research ArticleOpen accessIn the abstractPsoriasis Detection Using Skin Color and Texture FeaturesNidhal K. El Abbadi, Nizar Saadi Dahir, Muhsin A. AL-Dhalimi, Hind RestomProblem statement: In this study a skin disease diagnosis system was developed and tested. The system was used for diagnosis of psoriases skin disease. Approach: Present study relied on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin diseases. We used feed forward neural networks to classify … …Journal of Computer Science, Vol. 6, Issue 6 · 30 Jun 2010 · 8,290 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 abstractChange Detection Using Neural Network with Improvement Factor in Satellite ImagesM. A. Fkirin, S. M. Badwai, Sayed A. MohamedProblem statement: The aim of this study is to investigate the applicability of using the neural network techniques in change detection of remotely sensed data. Approach: In addition, the tuning parameters of the network, such as encoding the output classes, adding the momentum term and learning rate, are investigated in order to achieve best network performance. Results: Neural network-based change … …American Journal of Environmental Sciences, Vol. 5, Issue 6 · 31 Dec 2009 · 6,648 accessesView PDFCite
Research ArticleOpen accessIn the abstractWeighted Semi-Blind Channel Identification by Cross Relation MethodMohamed Tahar Taba, S. FemmamProblem statement: The bandwidth efficiency of many communication systems could be improved if the transmission channel was estimated blindly without resort to training sequences. GMSK was a spectrum-efficient modulation scheme and it was adopted as the modulation standard of GSM systems. Approach: However, because of its phase modulation, Gaussian filtering and partial response signalling properties, Results: The simulation results showed … …American Journal of Applied Sciences, Vol. 6, Issue 6 · 30 Jun 2009 · 6,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Analysis of Structures Using Neural NetworksN. Ahmadi, R. Kamyab Moghadas, A. LavaeiIn the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR) and Back-Propagation Wavenet neural network (BPW), for approximating of dynamic time history response of … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,154 accessesView PDFCite