Essays about: "Spiking Neural Network"
Showing result 21 - 25 of 30 essays containing the words Spiking Neural Network.
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21. Critical Branching Regulation of the E-I Net Spiking Neural Network Model
University essay from Luleå tekniska universitet/Institutionen för teknikvetenskap och matematikAbstract : Spiking neural networks (SNN) are dynamic models of biological neurons, that communicates with event-based signals called spikes. SNN that reproduce observed properties of biological senses like vision are developed to better understand how such systems function, and to learn how more efficient sensor systems can be engineered. READ MORE
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22. Study of neural correlates of attention in mice with spectro-spatio-temporal approaches
University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)Abstract : While signatures of attention can be observed in widespread areas within and outside of cortex, the control of attention is thought to be regulated by higher cognitive brain areas, such as the prefrontal cortex. In their recent study on mice Kim et al. READ MORE
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23. Developing a spiking neural model of Long Short-Term Memory architectures
University essay from Lunds universitet/Fysiska institutionen; Lunds universitet/FörbränningsfysikAbstract : Current advances in Deep Learning have shown significant improvements in common Machine Learning applications such as image, speech and text recognition. Specifically, in order to process time series, deep Neural Networks (NNs) with Long Short-Term Memory (LSTM) units are widely used in sequence recognition problems to store recent information and to use it for future predictions. READ MORE
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24. Monte Carlo Optimization of Neuromorphic Cricket Auditory Feature Detection Circuits in the Dynap-SE Processor
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : Neuromorphic information processing systems mimic the dynamics of neurons and synapses, and the architecture of biological nervous systems. By using a combination of sub-threshold analog circuits, and fast programmable digital circuits, spiking neural networks with co-localized memory and computation can be implemented, enabling more energy-efficient information processing than conventional von Neumann digital computers. READ MORE
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25. Pattern recognition with spiking neural networks and the ROLLS low-power online learning neuromorphic processor
University essay from Luleå tekniska universitet/Institutionen för teknikvetenskap och matematikAbstract : Online monitoring applications requiring advanced pattern recognition capabilities implemented in resource-constrained wireless sensor systems are challenging to construct using standard digital computers. An interesting alternative solution is to use a low-power neuromorphic processor like the ROLLS, with subthreshold mixed analog/digital circuits and online learning capabilities that approximate the behavior of real neurons and synapses. READ MORE
