Essays about: "Spiking Neural Network"

Showing result 11 - 15 of 30 essays containing the words Spiking Neural Network.

1. 11. Exploring the column elimination optimization in LIF-STDP networks

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Mingda Sun; [2022]
   Keywords : SpikingNeuralNetwork SNN ; neuromorphiccomputing; memoryoptimization; Hebbian learning; Spike-timing-depend plasticity STDP learning; Spiking Neural Network SNN ; neuromorphic computing; minnesoptimering; Hebbisk inlärning; spike-timing-depend plasticity STDP inlärning;

   Abstract : 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. READ MORE

3. 12. Development and Evaluation of a Road Marking Recognition Algorithm implemented on Neuromorphic Hardware

   University essay from KTH/Datavetenskap

   Author : Santiago Bou Betran; [2022]
   Keywords : SpiNNaker; Neuromorphic Hardware; Spiking Neural Network; Computer vision system; Lane recognition; Autonomous driving; Line Recognition; Neuromorphic Vision Sensors; Third Generation Neural Networks; Algorithm Evaluation.; SpiNNaker; Neuromorfiska hårdvara; neuromorfiska pulserande neuronnät; Datorseende system; läser av körbanans; självkörande bilar; läser av linjer; dynamiska synsensorer; Tredje generation neuronnät; utvärdering av algoritmen.; Hardware Neuromórfico; Sistemas de visión por computador; Reconocimiento de Carril; Conducción autónoma; Sensores de visión neuromórfica; Redes neuronales de Impulsos; Redes Neuronales de Tercera Generación; Evaluación de Algoritmos.;

   Abstract : Driving is one of the most common and preferred forms of transport used in our actual society. However, according to studies, it is also one of the most dangerous. One solution to increase safety on the road is applying technology to automate and prevent avoidable human errors. READ MORE

4. 13. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Philipp Mondorf; [2022]
   Keywords : ;

   Abstract : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. READ MORE

5. 14. Stochastic spiking neural networks based on ferroelectric memory devices

   University essay from Lunds universitet/Fasta tillståndets fysik; Lunds universitet/Fysiska institutionen

   Author : Karolis Sulinskas; [2021]
   Keywords : SNN; FTJ; Stochastic SNN; Spiking neural network; Binary SNN; SNN simulation; Physics and Astronomy;

   Abstract : In the last decade the world has seen a massive explosion of activity in the ma chine learning field. While the benefits of machine learning are ever growing and more impressive, the drawbacks of the technology are becoming clear and can hardly be ignored. READ MORE

6. 15. Integrating a SpiNNaker 2 prototype on an embedded platform : Hardware design and firmware modification

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Mikael Hessel; [2021]
   Keywords : SpiNNaker 2; Embedded software; Printed circuit board design; Power supplies; Firmware development.; SpiNNaker 2; Inbyggda system; Kretskortsdesign; Strömförsörjning; Inbyggd mjukvara;

   Abstract : The field of neuromorphic computing concerns simulating the information processing of a brain in software or hardware on a computing platform. One neuromorphic platform that uses specialized hardware is SpiNNaker. It is an integrated circuit consisting of multiple general purpose processing cores that can run simulations of neurons. READ MORE