Titlebook: Artificial Neural Networks; International Worksh Alberto Prieto Conference proceedings 1991 Springer-Verlag Berlin Heidelberg 1991 Artifici

嘮叨

Methods for encoding in multilayer feed-forward neural networks,ities for each initial symbol may be explicitly computed. Although thermal noise may muddle the code, we show how it can statistically rid the result of unwanted sequences while maintaining the network accuracy within a given bound.

innovation

Forehead-Lift

Feminist Theory in Pursuit of the Publicl wave equation derived from the time-dependent Schr?dinger equation. With this, we offer a model that can be used to justify the Kohonen algorithm from quantum physics. The Kohonen algorithm therefore is a principal progress in neural network research. As the algorithm operates in a local and paral

Fraudulent

https://doi.org/10.1057/9780230100732ction (output) to an external stimulus (input), to be represented uniquely by the spatio-temporal, dynamic activation process which occurs in the network caused by the external stimulus. For a restricted class of activation processes, we are able to determine the resultant activation process caused

MULTI

https://doi.org/10.1057/9780230100732of optimum learning rate adjustement according to an adaptive procedure based on gradient method. The basic idea, very simple, which has already been successfully used in Signal Processing, is extended to 2 neural algorithms : Kohonen self-organizing maps and blind separation of sources (Hérault-Jut

Magisterial

https://doi.org/10.1007/978-3-030-59793-1ttern recognition. That is why, among the primary interest of neural network (NN) research, the global optimization problem has received distinctive attention. Nevertheless, most of the commonly implemented neural networks either fail to achieve the global optimum like the Hopfield model [3,4], or t

crease

,Resümee: Gender Gap in der Demokratie,resented. With it the number of iterations needed so that the network reaches a stable configuration is reduced to a high degree. The new convergence criterion is based on the network stability measurement in contrast to the weight variation which is defined by Rumelhart et al. Results obtained in a

Heterodoxy

Feministische Demokratietheoriearticular linear threshold boolean function, called . is considered, whose synaptic weights are restricted to only three values: ?1, 0, +1. Some results about the complexity of the circuits composed of such gates are reported. They show that this simple family of functions remains powerful in therm

致詞

GREEN

Feministische ErkenntnisProzesses we need and how to use these tools to solve the questions in the way to attain a more thorough understanding of neural computation in the brain. In this paper we comment on some points that could be of interest in the biological perspective of neural computation. First some methodological remarks