… PHASOR NETVORKS Here I study the perhaps simplest non-scalar network by using unitlength
2-vectors (phasors… The signals processed by the network are represented in the relative …

… In this paper, I propose and solve a class of related modelsin which the phasors are discrete
… Potts neural network lies in the cyclic group structure of the value-space of q-state phasors, …

… ) recurrent neural network (RNN) is used as a versatile tool for the high-speed phasor detection
… For the application as a phasor detector, a fast pseudo-gradient training is performed off-…

… In this letter, I analyse a simple type of network that uses unit-length 2-vectors (phasors) as
continuous local variables. The information that the network processes is represented in the …

… Thanks to the simplicity of our neural network, the training time of Phasor-… neural network
20 . Finally, we can note that the relative squared error of our “phasor-based” neural network is …

… composite neural networks which utilize synchronized phasor measurements to provide …
neural network for all fault locations, using a short window of realistic-precision post-fault phasor …

… using Big Data from multiple Phasor Measurement Units (PMUs)… models were variants of
Convolutional Neural Network (CNN) … Thus, we propose adopting convolutional neural network-…

… In this study, a phasor estimation method based on artificial neural networks is proposed,
which will provide fast response time and accuracy. The method uses the multilayer perceptron …

… the artificial neural network (ANN) classifier, which is provided with synchronised phasor …
An excessive number of data frames are generated in the phasor data concentrator. Before …

… neural states. Noest proposed a model composed of extended neural elements called “phasor,”
and investigated properties of the model on the basis of the mean field theory A phasor …