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Search results for: neural network
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Year: 2022, Volume: 22, Number: 1
... within the dataset is very ï‚· The success of Recurrent Neural Networks (RNN) in similar to normal traffic ... A Hybrid Deep Learning Approach for Intrusion Detection in IoT Networks Murat EMEÇ, Mehmet Hilal Ã-ZCANHAN Department of Computer ... . With increasing mission- every IoT device on the network. Therefore, IoT devices are critical IoT data ...
Year: 2019, Volume: 19, Number: 2
... A Diagonally Weighted Binary Memristor Crossbar Architecture Based on Multilayer Neural Network for Better Accuracy Rate in Speech Recognition Application ... by Hewlett-Packard lab and completely made based on multilayer neural networks is proposed in the speech in 2008, has ... a new research field in applying the recognition application. Here, the memristor crossbar circuit memristor device to neuron ...
Year: 2023, Volume: 23, Number: 2
... examines classes of epilepsy. the performance of the convolutional neural network (CNN) In general, two tasks ... a dataset of features extracted from the EEG convolutional neural networks and support vector machines. signal, and the ... is trained with a dataset of Scalogram In addition, efficient heuristics for selecting electrodes are images from the EEG ...
Year: 2017, Volume: 17, Number: 3
... contains a USB interfaced multichannel learning methods such as Artificial Neural Networks (ANN) data acquisition (DAQ) ... and a graphical user interfaced [1 ], [2 ], [7-9], decision trees ( ... are many powerful automatic power quality technique combined with neural network model to build the detection and recognition systems developed ...
Year: 2007, Volume: 7, Issue: 1
... . Autonomous Adaptive Control Method//Optical Memory and Neural [14] Nesteruk G. Ph., ... Kupriyanov M. C. (2003) Neural-fuzzy systems Network, Vol. 9, No 2,- ... ), Number 1 (27), 2007 Adaptive Networks Safety Control on Fuzzy Logic Vadim MUKHIN1, Elena ...
Year: 2018, Volume: 18, Number: 3
... Engineering Volume 18, Number 3, 2018 Pulse Coupled Neural Network based Near- Duplicate Detection of Images ( ... copyright protection, feature extraction, image processing, neural networks. I. INTRODUCTION a) Original Image b ... ND Image In this modern era, exposures to social network and in Figure 1. Example of ND Image ...
Year: 2020, Volume: 20, Number: 2
... The ARIMA is widely Machine (SVM), Autoregressive Neural Network, LSTM, used because of its simplicity ... a prediction model for the models such as artificial neural networks (ANNs) have been activities of companies [ ... ] using the exponential proposed [10]. The ANNs can be used to predict the next correction, ...
Year: 2014, Volume: 14, Number: 1
... the model performed by Learning (ML) and Artificial Neural Networks (ANN) have Multilayer Perceptron classifier has ... best performance been applied to solve the STLF problems [1]. compared to the models of other classifiers ... function for an artificial neural functioning of the developed neural network (NN) method network in their study. ...
Year: 2019, Volume: 19, Number: 4
... , pp. 452-454, August 2006. doi: neural network for forecasting electricity demand," Energies, ... the stated problem are explained. Design of the matching networks For a dual band operation matching network design with ... Volume 19, Number 4, 2019 Tri-band Impedance Matching Network Design Using Particle Swarm Optimization Algorithm Sadık ÜLKER Electrical ...
Year: 2016, Volume: 16, Number: 3
... on temperature dynamics from the information provided by the artificial neural networks can be useful to deal with this train-test ... produced by the partition methods. Each problem, because of their ability to represent both linear and model adjusts ... of the test samples. In this paper different neural network models are analyzed, including non-linear autoregressive neural networks ...
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