neural networks
Top PDF neural networks:
Time series modeling and synchronization using neural networks
... years, neural networks have found interesting applications in the field of time series modeling and ...of neural networks when comparted with chaotic ...and neural approximate models. ...
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Pattern recognition in medical images using neural networks
... sense, neural networks are extremely useful, since not only are they capable of recognizing patterns with the aid of the expert, but also of generalizing the information contained in the input data, thus ...
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Keyword identification in spanish documents using neural networks
... these neural networks were trained using 20 hidden neurons, a maximum of 50 epochs, and the logistic function as activation function in the hidden and output ...
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TítuloDeep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
... Feedforward Neural Networks (DFNN), Deep Belief Networks (DBN), Deep AutoEncoder Networks, Deep Boltzmann Machines (DBM), Deep Convolutional Neural Networks (DCNN) and Deep ...
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A parallel approach for backpropagation learning of neural networks
... backpropagation neural networks using a pattern partitioning scheme with a set-training ...small neural net selected for the testing case a substantial acceleration ranging from 4 to more than ten ...
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TítuloArtificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
... This paper proposes a new whole and distributed integration approach between Artificial Neural Net- works (ANNs) and Databases (DBs) taking into account the different stages of the former’s lifecycle (training, ...
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Image compression for medical diagnosis using neural networks
... Although out of the scope of this work, it is possible to use pattern representations to work o n colour images. In this case, an increase of training time produced by the increase in size of the neural network, ...
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Custom architectures for fuzzy and neural networks controllers
... The synchronous or asynchronous feature of the Hopfield ANN is achieved by the microprogram. In the first case the neurons are all updated in each clock cycle. In the second, the neurons are updated sequentially. This ...
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Neural networks applied to wireless communications
... Neural network-based models are nowadays seen as a potential alternative for modeling electronics elements having medium-to-strong memory effects along with high-order nonlinearity. NNs are preferred over ...
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Deep learning applied to cryptocurrencies prices one step forecast
... investigated_the_use_of neural networks for one-step time series forecasting_on cryptocurrencies ...Convolutional Neural Networks (CNN) models are put to test to see if binary ...
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Playing the Imitation Game With Deep Learning
... neural networks, there’s no mathematical guar- antee that the training procedure will ever find the best set of ...recurrent neural networks are proving exceptionally ...
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