complex artificial neural network
Combined Complex-Valued Artificial Neural Network (CCVANN)
... single, neural network ...for neural network models (SNN) that consist of a combination of the candidate neural ...of artificial neural ...combining neural ...
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Artificial Neural Network Analysis in Food Science
... of network data in a wide variety of research disciplines has made complex network analysis a rapidly growing research area ever since two seminal publications in the late 1990s uncovered fundamental ...
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Adaptive Channel Equalizer using Combination of FIR and Functional Link Artificial Neural Network for Complex Signals
... link artificial neural (FLANN) network (CFFLANN) capable of equalizing complex multilevel ...less complex structure and high convergence ...
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FPGA Implementation of Artificial Neural Network
... Spiking Neural Networks – Spiking neural networks (SNNs) are models which explicitly take into account the timing of ...The network input and output are usually represented as series of spikes (delta ...
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Stability Assessment in Power Network Using Artificial Neural Network
... Presently, artificial neural networks (ANNs) has gained a lot of interest from researchers in recent years as a tool for voltage stability assessment ...learn complex non-linear relationships through ...
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Project Selection: Artificial Neural Network Approach
... Among the primary elements for maintenance and thriving operations of companies and for every country aspiring to develop its state’s competitiveness is R&D.In spite of this, owing to constrained budgets and ...
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Biometric Identification Using Artificial Neural Network
... Biometrics Identification is the recent used technology used authenticate the person's identity. Biometric identification has eventually a much broader relevance as computer interface becomes more natural. Biometrics ...
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Artificial Neural Network Learning Techniques: A Survey
... Artificial Neural Network works on two phases: ...humans. Neural networks comprises of three layers such as input layer, output layer and hidden ...more complex that even humans cannot ...
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CSI Neural Network: Using Side-channels to Recover Your Artificial Neural Network Information
... the neural network architectures ...the network during the training ...the network with trained weights is a desirable target for the ...the neural network architecture instead ...
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Diabetes Prediction Using Artificial Neural Network
... paper, artificial neural network was used to predict ...Using artificial neural networks model we can design and implement complex medical processes using ...general, ...
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Robust artificial neural network for reliability analysis
... Nowadays, numerical models are increasingly used to analyze and predict the performance of complex critical systems. Concurrently, engineering practitioners are concerned with un- certainty, which is inherent to ...
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Artificial Neural Network for Predicting Flood : A Review
... ANNs were first introduced in water resources research for their use to predict monthly water consumption and to estimates occurrences of floods. Since then ANNs have been used for a number of different water resources ...
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Building and Improving Artificial Neural Network Classifier
... for neural network it decides which neurons to activate or ...in neural network so based on the output requirement we can use ...for neural network there exits several ...
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1. Secret writing by artificial neural network
... the neural system as well as the input weights makes this cryptography technique strong and apt for actual ...on complex computations which require significant CPU and memory ...
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Diabetic Retinopathy Using Artificial Neural Network
... more complex patterns in the data as it is propagated thought the ...the network is given a task to recognize a face, the first hidden layer might act as a line detector, the second hidden takes these lines ...
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Power Flow Analysis by Artificial Neural Network
... ANN gathers stores and generalizes information by learning sequence, like human brain. Learning sequence is consisting of learning algorithms which supplies to renew the weights of ANN to reach the target. Generalization ...
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Email Classification Using Artificial Neural Network
... Artificial Neural Networks (ANNs) can resemble with the human brain which refers to interconnected networks of nodes, which manipulate data from input to output ...computationally complex and the ...
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Robust artificial neural network for reliability and sensitivity analysis of complex non-linear systems
... a complex and expensive mathematical model of the Site Ion eXchange Effluent Plant (SIXEP)(see [33]) situated on the nuclear fuel reprocessing and decommissioning site at Sellafield, ...most complex nuclear ...
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Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease
... The increasing availability of electronic medical infor- mation that can be collected and used for pattern recog- nition has created new opportunities to improve diagnoses and predictions of disease outcomes [12–15]. ...
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Intelligent Neural Network For Bacteria Classification: An Innovation In Artificial Neural Network
... identification. Neural network has been exoploted as a soft-computing based classifier for the taxonomy of pathogenic ...Intelligent Neural Network has been considered as a mathematical model ...
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