Sökning: "Hebbisk inlärning"
Hittade 3 uppsatser innehållade orden Hebbisk inlärning.
1. Regression with Bayesian Confidence Propagating Neural Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER
2. Exploring the column elimination optimization in LIF-STDP networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Spiking neural networks using Leaky-Integrate-and-Fire (LIF) neurons and Spike-timing-depend Plasticity (STDP) learning, are commonly used as more biological possible networks. Compare to DNNs and RNNs, the LIF-STDP networks are models which are closer to the biological cortex. LÄS MER
3. Sequence Disambiguation in a Brain-Like Recurrent Neural Network with Local Associative Learning
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The learning of sequences is a fundamental ability of biological networks. While there are many artificial networks that are able to successfully learn sequences, it is of particular interest to study networks that attempt to do so in a manner similar to how it is done by a human brain. LÄS MER