Under the sustainability today, almost everyone understands the environmentally friendly use of energy-efficient solutions, which are alternatives to private transport

Keywords: Spoken Language Understanding (SLU), intent detection, Convolutional Neural Networks, residual connections, deep learning, neural networks.. 1

Rectified neural units were recently applied with success in standard neural networks, and they were also found to improve the performance of Deep Neural Networks on tasks like

Some well results have just appeared, for example, in [1-5], for stochastic delayed Hopfield neural networks and stochastic Cohen-Grossberg neural networks, the linear matrix

Key words and phrases: scheduling theory, artificial neural networks, Hopfield neural network, total weighted tardiness problem, quadratic

Marcus Liwicki: Applications of recurrent and BLSTM neural networks Slide

logistic regression, non-linear classification, neural networks, support vector networks, timeseries classification and dynamic time warping?. o Linear and polynomial, one

Xue, “Global exponential stability and global convergence in finite time of neural networks with discontinuous activations,” Neural Process Lett., vol.. Guo, “Global

An Artificial Neural network (ANN) is a mathematical model that simulates the computational model like the biological neural networks.. It consists of interconnected artificial

After some centralization and normaliza- tion we independently categorized the 2D slices with convolutional neural networks (traditional and residual feed-forward networks) and

Abstract: The main subject of the study, which is summarized in this article, was to compare three different models of neural networks (Linear Neural Unit

Using the results, some experimental data sets were generated for training, validation and test purposes of neural networks.. Five networks were trained and their results

Abstract: The paper is focused especially on presenting possibilities of applying off-line trained artificial neural networks at creating the system inverse models that are used at

We achieved the best results of training the MLP network using network configuration 3-10-1 (which means: 3 input neurons, 10 neurons in hidden layer, 1 output

Unfortunately, these novel techniques fell short of the expectations for two reasons: (i) in the case of statistical optimization the associated computational

Keywords: algorithmic trading, financial time series, neural networks, independent component analysis, mean reverting portfolio.. JEL

In this paper, we also apply deep neural networks to convert the ultrasound video of the tongue movement to speech.. Although some early studies used simple fully connected

Unsupervised fault diagnosis of rolling bearings using a deep neural network based on generative adversarial networks,”..