Lee, S.W., Kim, Y.J.: A New Type of Recurrent Neural Network for Handwritten Character Recognition. In: Proc. 3rd International Conference on Document Analysis and Recognition, vol. 1 (1995)A New Type of Recurrent Neural Network for Handwritten Character Recognition - Lee, Kim - 1995...
A new kind of recurrent neural network is presented for solving the Lyapunov equation with time-varying coefficient matrices. Different from other neural-computation approaches, the neural network is developed by following Zhang et al.'s design method, which is capable of solving the time-varying ...
Hsu, Y.-L., Wang, J.-S.: A Wiener-type recurrent neural network and its control strategy for nonlinear dynamic applications. Journal of Process Control 19, 942–953 (2009) View ArticleHsu, Y.-L., Wang, J.-S.: A Wiener–type recurrent neural network and its control strategy for ...
For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN...
Engineering Applications of Neural Networks-inns Eann-sig International ConferenceAllam F, Nossai Z, Gomma H, Ibrahim I, Abdelsalam M. A Recurrent Neural Network Approach for Predicting Glucose Concentration in Type-1 Diabetic Patients. IFIP Advances in Information and Communication Technology. 2011; ...
For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN...
The prediction capability of recurrent-type neural networks is investigated for real-time short-term prediction (nowcasting) of ship motions in high sea st
The collective behaviour of neural networks depends on the cellular and synaptic properties of the neurons. The phase-response curve (PRC) is an experimentally obtainable measure of cellular properties that quantifies the shift in the next spike time of a neuron as a function of the phase at ...
Ching-Hung, L., Chang, H., Ting Kuo, C., Chieh Chien, J., Wei Hu, T.: A Novel Recurrent Interval Type-2 Fuzzy neural Network for Nonlinear Channel Equilization. In: Proceeding of the Int. MultiConf. of Eng. and Computer Sci., pp. 7–12 (2009)...
On the timescale of sensory processing, neuronal networks have relatively fixed anatomical connectivity, while functional interactions between neurons can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli could lead those networks...