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Hebbian Learning Links Memory and Perception

A collaboration between SISSA's Physics and Neuroscience groups has taken a step forward in understanding how memories are stored and retrieved in the brain. The study, recently published in Neuron, ...
Scientific Research Publishing

Choe, Y. (2014) Hebbian Learning. In: Jaeger, D. and Jung, R., Eds., Encyclopedia of Computational Neuroscience, Springer, 1-5.

ABSTRACT: Purpose: This study aimed to enhance the prediction of container dwell time, a crucial factor for optimizing port operations, resource allocation, and supply chain efficiency. Determining an ...
Frontiers

Learning algorithms for oscillatory neural networks as associative memory for pattern recognition

Alternative paradigms to the von Neumann computing scheme are currently arousing huge interest. Oscillatory neural networks (ONNs) using emerging phase-change materials like VO 2 constitute an ...
eLife

Rapid learning of predictive maps with STDP and theta phase precession

The predictive map hypothesis is a promising candidate principle for hippocampal function. A favoured formalisation of this hypothesis, called the successor representation, proposes that each place ...
IEEE

Markov Chain Hebbian Learning Algorithm With Ternary Synaptic Units

Abstract: In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due, in part, ...
Europe PMC

Expert- Independent Initial Weights Assignment Technique for Learning Fuzzy Cognitive Map With Hebbian Learning Algorithms

Fuzzy Cognitive Maps (FCMs) are single layer neural network-like Supervised Machine Learning Algorithm which can be used as a tool for modelling dynamic systems in a graphical cause-effect ...