Essays about: "synaptic"
Showing result 1 - 5 of 51 essays containing the word synaptic.
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1. Optical Communication using Nanowires and Molecular Memory Systems
University essay from Lunds universitet/Fysiska institutionen; Lunds universitet/SynkrotronljusfysikAbstract : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. READ MORE
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2. Harnessing the Power of Voltage-dependent Synaptic Plasticity (VDSP): A Novel Paradigm for Unsupervised Learning in Neuromorphic Systems
University essay from Luleå tekniska universitet/DatavetenskapAbstract : .... READ MORE
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3. Quantifying the Impact of Synaptic Delay and Neuronal Refractory Period on Criticality in Hierarchical Modular Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Self-organized brain criticality suggests that the brain is able to operate near a critical point.With compelling evidence supporting the theory, it is important to understand whichbiological mechanisms are required for critical dynamics to occur. READ MORE
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4. A Bayesian Bee Colony Algorithm for Hyperparameter Tuning of Stochastic SNNs : A design, development, and proposal of a stochastic spiking neural network and associated tuner
University essay from Uppsala universitet/Signaler och systemAbstract : With the world experiencing a rapid increase in the number of cloud devices, continuing to ensure high-quality connections requires a reimagining of cloud. One proponent, edge computing, consists of many distributed and close-to-consumer edge servers that are hired by the service providers. READ MORE
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5. Modelling synaptic rewiring in brain-like neural networks for representation learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This research investigated the concept of a sparsity method inspired by the principles of structural plasticity in the brain in order to create a sparse model of the Bayesian Confidence Propagation Neural Networks (BCPNN) during the training phase. This was done by extending the structural plasticity in the implementation of the BCPNN. READ MORE