Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 23 for “"integrate-and-fire"”.
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Design and Optimization of Temporal Encoders using Integrate-and-Fire and Leaky Integrate-and-Fire Neurons
… encoders receive an analog signal as an input and generate a spike or spike trains as their output. The proposed temporal encoders use latency and Inter-Spike Interval (ISI) encoding and are expected to produce a highly sensitive hardware implementation of time encoding to preprocess signals …
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Sample Path Analysis of Integrate-and-Fire Neurons
… analysis has proven instrumental in understanding the coding strategies of early neural processing in various sensory modalities. Yet, at higher levels of integration, it fails to help in deciphering the response of assemblies of neurons to complex naturalistic stimuli. If neural activity …
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Integrate-and-fire modelling of neuronal systems with modulatory properties
… Nevertheless, their high dimensionality and number of parameters complicate mathematical analysis and numerical simulation. Integrate-and-fire models have been successful at the accurate prediction of spike times at a reduced computational cost. However, this success comes at the cost of …
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Travelling waves modulated by resonant currents in laterally-inhibited grids of leaky integrate-and-fire neurons
… of neural activity are a biologically salient and analytically tractable dynamic of networks of neurons. They have been observed experimentally across the whole brain as well as at smaller scales, linked to functions as diverse as visual processing, motor coordination, and situating oneself in …
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Digital pulse processing
… approach for processing pulse signals from an integrate-and-fire system directly in the time-domain. Processing is deterministic and built from simple asynchronous finite-state machines that can perform general piecewise-linear operations. The pulses can then be converted back into an analog or …
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Two problems about coupled oscillators: transient dynamics and swarming
… of such oscillators. The first is Peskin’s integrate-and-fire model. We focus on the transitory behavior, showing that in its infancy, synchrony looks much like aggregation. In the second model, we consider oscillators which ad- just their positions in space as well as their phases. We show …
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Modelling the synaptic plasticity underlying habituation, sensitization and classical conditioning of the Aplysia Californica Gill Siphon withdrawal reflex
… models, including the Hodgkin Huxley equations and the Leaky Integrate-and-Fire model. Also included is a brief description of some neural coding schemes. The next chapter explains the basic functioning of synapses and introduces some common forms of synaptic plasticity. This is followed by a …
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Dynamics of a fully stochastic discretized neuronal model with excitatory and inhibitory neurons
We consider here an extension and generalization of the stochastic neuronal network model developed by DeVille et al.; their model corresponded to an all-to-all network of discretized integrate-and-fire excitatory neurons where synapses are failure-prone. It was shown that this model exhibits …
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Optically injected dual state quantum dot lasers
The spikes and pulses observed in biological neurons have similar characteristics to the excitable pulses seen in optically injected lasers. This thesis investigates the feasibility of optically injected dual state quantum dot lasers as artificial photonic neurons. Photonic waveguides are not as …
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Dynamics of bankrupt stocks
… of the Hard-to-borrow feedback for the buy-in demand, the bankrupt stocks could exclude the diffusive effects. This nice property would modify the Marco Avellaneda and Mike Lipkin's jump-diffusion model for the Hard-to-Borrow stocks into the pure jump systems with stochastic intensity. Under this …
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Enabling Energy-Efficient Hybrid CMOS and Embedded Memory Accelerators for Neuromorphic Computing at the Edge
… advances in autonomous driving, computer vision, and IoT, but is limited by the inefficiencies of conventional von Neumann architectures. The physical separation of memory and processing creates a performance bottleneck, with high energy and latency costs. This dissertation investigates hybrid …
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Neuromorphic deep convolutional neural network learning systems for FPGA in real time
… speech recognition, natural language processing, and audio recognition, among others. In image vision, convolutional neural networks stand out, due to their relatively simple supervised training and their efficiency extracting features from a scene. Nowadays, there exist several implementations of …
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Growing synfire chains with triphasic spike-time-dependent plasticity
… into functional networks capable of intricate and accurate information processing is one of the biggest and most interesting challenges in neuroscience today. To approach this challenge, it is necessary to address the problem one structure at a time. In this thesis the focus is the development …
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Biosignal Recording with Integrated Circuits
This dissertation presents novel integrated circuits designed to improve signal recording and processing in biomedical applications. The primary focus is on improving low-noise, low-power amplifiers, where a comparison of existing topologies reveals the trade-offs between noise, power consumption …
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An electrophysiological basis for human memory
… processes underlying memory formation and retrieval in humans remains very poorly understood, and in turn, limits our abilities to provide effective therapy for patients suffering from these disorders. Here, we endeavored to investigate the underpinnings of human memory through …
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Dynamics of phase locking in neuronal networks in the presence of synaptic plasticity
… from the combined effects of individual cells and synaptic connections whose properties change dynamically. The properties of individual cells and synapses can often be characterized by driving the cell or synapse with inputs that arrive at different phases or frequencies, thus producing a …
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Inference of functional neural connectivity and convergence acceleration methods
… but not the intracellular voltage, of thousands of neurons gives us an opportunity to start filling that gap. In Chapter 2, I present a method for the inference of the parameters of the leaky integrate-and-fire (LIF) model featuring time-dependent currents and conductances based only on the …
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A Heterosynaptic Spiking Neural System for the Development of Autonomous Agents
… first proposed three quarters of a century ago and the concepts developed by the pioneers still shape the field today. The first generation of neural systems was developed in the nineteen forties in the context of analogue electronics and the theoretical research in logic and mathematics that …
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Loss of synchrony in an inhibitory network of type-I oscillators
… synaptic interaction plays in the generation and regulation of coherent rhythmic activity in a variety of neural systems. While recent work revealed the synchronizing influence of inhibitory coupling on the dynamics of many networks, it is known that strong coupling can destabilize …
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Identification of Dendritic Processing in Spiking Neural Circuits
… taking place at the level of dendritic trees and dendritic branches of neurons. This evidence suggests that, in addition to inferring the connectivity between neurons, identifying analog dendritic processing in individual cells is fundamentally important to understanding the underlying …
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