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23 757 (0,184s)

Result

Assembly Neural Network with Nearest-Neighbor Recognition Algorithm

An assembly neural network based on binary Hebbian rule is suggested for pattern recognition. The network consists of several sub-networks according to the number of classes to be recognized. Each sub-network consists of se...

BA - Obecná matematika

  • 2005
  • Jx
Result

Binary Factorization by Neural Autoassociator.

He unsupervised learning of feature extraction in high-dimensional patterns is a central problem for neural network approach. Feature extraction is the procedure which maps original patterns into the features (or factors) space of reduced dimension. ...

JC - Počítačový hardware a software

  • 2003
  • D
Result

On Informational Characteristics of Willshaw-Like Auto-Associative Memory.

A sparsely encoded Willshaw-like attractor neural network based on the binary Hebbian synapses is investigated analytically and by computer simulations. A special inhibition mechanism which supports a constant number of active neuro...

BA - Obecná matematika

  • 2002
  • Jx
Result

Neural Network Binary Factorization as a Tool for Large Dataset Clustering

that Hebbian learningin Hopfield-like neural network is a natural procedure for binary a single inhibitory neuron with bi-directional Hebbian synapses. Due to additional......

BB - Aplikovaná statistika, operační výzkum

  • 2004
  • D
Result

Binary Factorization by Neural Autoassociators.

In this paper we demonstrate that Hebbian learning in Hopfield-like neural network is a natural procedure for binary factorization. Due to this learning, factors become the attractors of network dynamics. The neurodynamics is analyz...

BD - Teorie informace

  • 2003
  • D
Result

Binary Factorization in Hopfield-Like Neural Autoassociator: A Promising Tool for Data Compression.

Proposed approach of data compression is based on feature extraction procedure which maps original patterns into features (factors) space of reduced, possibily very small, dimension. It is shown that Hebbian unsupervised learning of Hopfield...

JD - Využití počítačů, robotika a její aplikace

  • 2003
  • D
Result

Binary Factorization in Hopfield-Like Neural Networks: Single-Step Approximation and Computer Simulations

The unsupervised learning of feature extraction in high-dimensional patterns space is a central problem for the neural network approach. Feature extraction is a procedure which maps original patterns into the feature (or factor) space of reduced dime...

BA - Obecná matematika

  • 2004
  • Jx
Result

Uncertainty Propagation in Fuzzy Grey Cognitive Maps With Hebbian-Like Learning Algorithms

with the problem of uncertainty propagation in FGCM dynamics with Hebbian learning. In addition, this paper applies differential Hebbian learning (DHL) and balanced DHL to FGCMs that the nonlinear Hebbian learning is the c...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • Jimp
  • Link
Result

Attractor Neural Network Combined with Likelihood Maximization Algorithm for Boolean Factor Analysis

When large data sets are analyzed, the pursuit of their appropriate representation in the space of lower dimension is a common practice. Boolean factor analysis can serve as a powerful tool to solve the task, when dealing with binary data. H...

IN - Informatika

  • 2012
  • D
Result

Neural PCA and maximum likelihood hebbian learning on the GPU

This study introduces a novel fine-grained parallel implementation of a neural principal component analysis (neural PCA) variant and the maximum Likelihood Hebbian Learning (MLHL) network designed for modern many-core graphics processing uni...

IN - Informatika

  • 2012
  • D
  • Link
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