neural network-based L/sub 1/-norm optimisation approach
Neural Network based Approach for Recognition of Text Images
... the network. The table 1 displays the results obtained from the ...the network is set at ...and 1 bitmap file is taken for testing in which letters are arranged in the form of ...of ...
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A Comprehensive Evaluation Approach Based on AHP BP Neural Network for Resource Allocation in Distributed Satellite Cluster Network
... BP neural network is an efficient method to calculate evaluation result by adjusting the weight and threshold ...an approach combining AHP and BP neural network is proposed to decrease ...
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Prediction models in the design of neural network based ECG classifiers: A neural network and genetic programming approach
... ECG based on a configuration of bi-group NNs (BGNNs) ...Each network has the ability to be trained to specifically detect the presence (or absence) of one of the aforementioned diagnostic categories and ...
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NEURAL NETWORK BASED MATCHING APPROACH FOR IRIS RECOGNITION
... Iris recognition has been considered as one of the most reliable biometrics technologies in recent years due to its high reliability in person identification. In this paper, an iris recognition system has been proposed. ...
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Analysis of Earth Embankment Structures using Performance-based Probabilistic Approach including the Development of Artificial Neural Network Tool.
... The levee network in the Sacramento-San Joaquin Delta supports an exceptionally rich agricultural area (over a $500 million annual crop value). Currently, the risk of levee failure in this area from extreme storms ...
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Real-time face recognition system using radial basis function neural networks
... Low Level Analysis ,..-- Feature-Based r-- Feature Analysis Approach .._ Active Shape Model Face Detection 1-- Linear Subspace r- Image-Based '-- Method Neural Network Approach - Statist[r] ...
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Product Yields Prediction of Tehran Refinery Hydrocracking Unit Using Artificial Neural Networks
... RBF neural network architectures in creating a model of the hydrocracking ...Our approach is based on: (1) formulation of an artificial neural network (ANN) with the input ...
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Application and testing of the L neural network with the self-consistent magnetic field model of RAM-SCB
... theorem based on which equation (3) is derived, (4) errors in the K parameter due to the imperfec- tion of the magnetic field model, and (5) errors in the L ∗ calculation due to the magnetic field model as ...
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NEURAL NETWORK BASED APPROACH FOR RECOGNITION FOR DEVANAGIRI CHARACTERS
... Neural networks have been trained to perform complex functions in various fields of application including pattern recognition, identification, classification, speech, vision and control systems. Today ...
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An Approach Based On Artificial Neural Network for Data Deduplication
... Data mining methods and techniques utilizing software or algorithms called data mining tools, effectively mine and provide an edifying and useful analysis [7]. Predictive and Descriptive are two types of data mining ...
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A Neural Network based Approach to Automatic Post Editing
... a neural network based auto- matic post-editing (APE) system to im- prove raw machine translation (MT) out- ...Our neural model of APE (NNAPE) is based on a bidirectional recurrent neu- ...
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Peak to peak exponential direct learning of continuous time recurrent neural network models: a matrix inequality approach
... dynamic neural network models with disturbance. Dynamic neural network models trained by the proposed P2PEDLL based on matrix inequality formulation are exponentially stable, with a ...
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Transformer incipient fault prediction using combined artificial neural network and various particle swarm optimisation techniques
... In one of the previous works, ANN was combined with the knowledge based of expert sys- tem for transformer fault diagnosis from DGA analysis [4]. The combination of both methods yields better performance than each ...
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An Extensive Empirical Evaluation of Character Based Morphological Tagging for 14 Languages
... investigates neural character- based morphological tagging for lan- guages with complex morphology and large tag ...character- based word vectors using recurrent (RNN) and convolutional (CNN) ...CNN ...
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KNOWLEDGE EXTRACTION METHOD USING STOCHASTIC APPROACHES IN GOOGLE MAPS
... Conventional images used for change detection, mostly remotely sensed images, were multispectral images that captured data at different wavelengths from the electromagnetic spectrum. Hence, initial techniques were ...
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C++ Neural Networks and Fuzzy Logic Valluru B Rao pdf
... the network, where the edge is from one node to ...the network output are declared ...a neural network, the outputs of neurons in one layer become the inputs for neurons in the next ...the ...
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AN EFFICIENT SUPER PEER SELECTION ALGORITHM FOR PEER TO PEER (P2P) LIVE STREAMING NETWORK
... Neural Network based on Nonlinear Auto- Regressive model (NAR) has been utilized to get the dynamic response of the ...model. Based on the Table 4, the lowest MSE founded in neurons (NE) 6 is ...
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Deep Learning in Computer Aided Diagnosis of MDD
... Since we are handling EEG data, preprocessing the input dataset will involve elimination of noise that is present in it, so that the available data is closer to the real values measured. Preprocessing on EEG data can ...
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Segmentation of Lung Images using Region Based Neural Networks
... which identifies the sets of pixels which are connected and continuous in nature present in the image. This can be done using some threshold based operations. Region growing is an operation, which can be done by ...
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Remarks on Direct System Identification Using Hypercomplex–Valued Neural Network with Application to Time–Series Estimation
... for neural networks has attracted increasing attention from engineering re- search fields because it helps to learn to handle a wide variety of geometric objects and their transformation in the form of ...
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