Results 261 to 270 of about 5,989,108 (296)

Neural network for computing GSVD and RSVD

Neurocomputing, 2021
Abstract This paper presents the neural dynamical network to compute the generalized and restricted singular value decompositions (GSVD/RSVD) in the regularization methods for ill-posed problems. The neural network model is defined by ordinary differential equations (ODE) which can be solved by many state-of-the-art techniques.
Liping Zhang 0005, Yimin Wei 0001, Eric King-Wah Chu   +2 more
openaire   +2 more sources

On the computational power of neural networks and neural automata

1990 IJCNN International Joint Conference on Neural Networks, 1990
The problem of which functions can be computed by a neural network is considered. The answers to this question determine the capabilities and limitations of a neural network as a general-purpose computer. A computation process is defined as the dynamic motion of input states to output states.
openaire   +1 more source

Computing with neural networks

IEEE Potentials, 1993
The resurgence of interest in neural networks is discussed. This interest is prompted by two facts. First, the nervous systems of simple animals can easily solve problems that are very difficult for conventional computers. Second, the ability to model biological nervous system functions using man-made machines increases understanding of that biological
M.N.O. Sadiku, M. Mazzara
openaire   +1 more source

Computing with Neural Networks

Science, 1987
Gail A. Carpenter, Michael A. Cohen, Stephen Grossberg   +2 more
  +8 more sources

Computation, Cognition, and Neural Networks

1995
Computation and Cognition. To understand computing with neural networks and how cognitive processes can be implemented in this way, it is imperative to distinguish between two kinds of machines and the forms of computation they produce: Finite-state automata (FA’s), and machines such as the Turing machine (TM) or the pushdown automaton (PA).
openaire   +1 more source

Neural Networks for Computer Systems

Proceedings of the 16th ACM International Conference on Systems and Storage, 2023
Alon Rashelbach, Ori Rottenstreich, Mark Silberstein   +2 more
openaire   +2 more sources

Neural Networks and Computing

2007
This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area.
Tommy W. S. Chow, Siu-Yeung Cho
openaire   +1 more source

Neural Network Trainer through Computer Networks

2010 24th IEEE International Conference on Advanced Information Networking and Applications, 2010
This paper introduces a neural network training tool through computer networks. The following algorithms, such as neuron by neuron (NBN) [1][2], error back propagation (EBP), Levenberg Marquardt (LM) and its improved versions are implemented in two different computing methods, traditional forward-backward computation and newly developed forward-only ...
Nam Pham, Hao Yu, Bogdan M. Wilamowski
openaire   +1 more source

Neural networks for shortest path computation and routing in computer networks

IEEE Transactions on Neural Networks, 1993
The application of neural networks to the optimum routing problem in packet-switched computer networks, where the goal is to minimize the network-wide average time delay, is addressed. Under appropriate assumptions, the optimum routing algorithm relies heavily on shortest path computations that have to be carried out in real time.
Mustafa K. Mehmet Ali, Faouzi Kamoun
openaire   +3 more sources

Neural Network and Neural Computing

Deep learning, a subset of AI, has gained popularity in various fields, including computer vision and NLP. It is based on artificial neural networks, which process multiple layers of data and extract high-level features automatically. Unlike traditional ML algorithms, deep learning can process large unstructured data and complex algorithms better than ...
Partha Ghosh, Suradhuni Ghosh
openaire   +1 more source