Sökning: "NEURON"
Visar resultat 1 - 5 av 158 uppsatser innehållade ordet NEURON.
1. Glucose Sensing and Differentiating Systems with Organic Electrochemical Neurons : A Future Outlook for Type 2 Diabetes
Master-uppsats, Linköpings universitet/Institutionen för teknik och naturvetenskapSammanfattning : In recent years great advances in the field of biomedical engineering and organic electronics have been achieved. One promising application would be the regulation of blood glucose concentration in type 2 diabetes patients. This application would eliminate medication and would improve the standard of life. LÄS MER
2. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER
3. Ru and RuO2 as bottom electrodes for HZO based FTJ’s
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Vår hjärna löser beräkningar som tar oss genom livet otroligt energieffektivt; den kör hela dagen runt på ungefär 12 watt. Jämför man med en vanlig dator som kräver ungefär 175 watt så är det inte ens nära[2]. Att uppnå hjärnans energieffektivitet är ett ambitiöst mål för dagens elektronik. LÄS MER
4. Comparing energy efficiency of Leaky integrate-and-fire and Spike response neuron models in Spiking Neural Networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Spiking Neural Networks (SNNs) are a type of neural network that is designed to mimic the way neurons function in our brains. While there have been notable advancements in developing SNNs, energy consumption hasn't been studied to the same extent. This gets especially relevant with steadily increasing network sizes. LÄS MER
5. Evaluating the Effects of Neural Noise in the Multidigraph Learning Rule
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : There exists a knowledge gap in the field of Computational Neuroscience, where many learning models for neural networks fail to take into account the influence of neural noise. The purpose of this thesis was to address this knowledge gap by investigating the robustness of the Multidigraph learning rule (MDGL) when exposed to two kinds of neural noise: external noise and internal noise. LÄS MER