Abstract. Compared to normal learning algorithms, for example backpropagation, the optimal bounded ellipsoid (OBE) algorithm has some better properties, such as faster convergence,...
We evaluate the effectiveness of neural networks as a tool for predicting whether a particular combination of preconditioner and iterative method will correctly solve a given spar...
Abstract. We present a model of a recurrent neural network, embodied in a minimalist articulated agent with a single link and joint. The configuration of the agent defined by one...
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA)...
Abstract—This paper presents the development and performance evaluation of a human-computer interface that enables a limb-disabled person to access a computer via neural signals....
Changmok Choi, Hyonyoung Han, Chunwoo Kim, Jung Ki...
— In the last decade, neural networks have been applied in Daily Load Forecasting. Nevertheless, two main problems are still present for using neural networks in this domain: fi...
Ivan Aquino, Cesar Oswaldo Perez Pinche, Jacquelin...
Abstract— Hardware implementations of Spiking Neural Networks are numerous because they are well suited for implementation in digital and analog hardware, and outperform classic ...
Benjamin Schrauwen, Michiel D'Haene, David Verstra...
— Association Rule Mining is a thoroughly studied problem in Data Mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the...
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...
The provision of embedding neural networks into software applications can enable variety of Artificial Intelligence systems for individual users as well as organizations. Previous...