Displaying similar documents to “Application of Neural-Net Computing to Transient Stability Assessment and Enhancement of Electric Power Systems”

Backpropagation generalized delta rule for the selective attention Sigma-if artificial neural network

Maciej Huk (2012)

International Journal of Applied Mathematics and Computer Science

Similarity:

In this paper the Sigma-if artificial neural network model is considered, which is a generalization of an MLP network with sigmoidal neurons. It was found to be a potentially universal tool for automatic creation of distributed classification and selective attention systems. To overcome the high nonlinearity of the aggregation function of Sigma-if neurons, the training process of the Sigma-if network combines an error backpropagation algorithm with the self-consistency paradigm widely...

Acoustic analysis assessment in speech pathology detection

Daria Panek, Andrzej Skalski, Janusz Gajda, Ryszard Tadeusiewicz (2015)

International Journal of Applied Mathematics and Computer Science

Similarity:

Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional...

Comparison of supervised learning methods for spike time coding in spiking neural networks

Andrzej Kasiński, Filip Ponulak (2006)

International Journal of Applied Mathematics and Computer Science

Similarity:

In this review we focus our attention on supervised learning methods for spike time coding in Spiking Neural Networks (SNNs). This study is motivated by recent experimental results regarding information coding in biological neural systems, which suggest that precise timing of individual spikes may be essential for efficient computation in the brain. We are concerned with the fundamental question: What paradigms of neural temporal coding can be implemented with the recent learning methods?...

A simplex trained neural network-based architecture for sensor fusion and tracking of target maneuvers

Yee Chin Wong, Malur K. Sundareshan (1999)

Kybernetika

Similarity:

One of the major applications for which neural network-based methods are being successfully employed is in the design of intelligent integrated processing architectures that efficiently implement sensor fusion operations. In this paper we shall present a novel scheme for developing fused decisions for surveillance and tracking in typical multi-sensor environments characterized by the disparity in the data streams arriving from various sensors. This scheme employs an integration of a...

An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection

Marcin Mrugalski (2013)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper presents an identification method of dynamic systems based on a group method of data handling approach. In particular, a new structure of the dynamic multi-input multi-output neuron in a state-space representation is proposed. Moreover, a new training algorithm of the neural network based on the unscented Kalman filter is presented. The final part of the work contains an illustrative example regarding the application of the proposed approach to robust fault detection of a...