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Showing 1 to 20 of 23 for “"STDP"”.

  1. Network Behavior Analysis of Spike Timing Dependent Plasticity (STDP) in Simulated Neural Networks

    … Spike Timing Dependent Plasticity (STDP) model to the weighted graph output from neural growth simulations and analyzes the resulting spike and weight changes over time. This preliminary investigation establishes a baseline process for understanding the effects of STDP on a neural …

    washington Repository record for Network Behavior Analysis of Spike Timing Dependent Plasticity (STDP) in Simulated Neural Networks (opens in a new tab)

  2. Network Structures Arising from Spike-Timing Dependent Plasticity

    Spike-timing dependent plasticity (STDP), a widespread synaptic modification mechanism, is sensitive to correlations between presynaptic spike trains, and organizes neural circuits in functionally useful ways. n this dissertation, I study the structures arising from STDP in a population of synapses …

    columbia-diss Repository record for Network Structures Arising from Spike-Timing Dependent Plasticity (opens in a new tab)

  3. Analog VLSI circuit design of spike-timing-dependent synaptic plasticity

    … First is the spike-timing-dependent-plasticity (STDP), a timing-based protocol that suggests that the efficacy of synaptic connections is modulated by the relative timing between presynaptic and postsynaptic stimuli. The second type is the Bienenstock-Cooper-Munro (BCM) learning rule, a classical …

    mit Repository record for Analog VLSI circuit design of spike-timing-dependent synaptic plasticity (opens in a new tab)

  4. Neural Networks for Control of Artificial Life Form

    … weights in the synaptic connections of neurons. STDP is the learning rule implemented to the network in this project. STDP adjusts the synaptic weights according to the precise timing of pre and postsynaptic spikes. The artificial life form itself has been designed to complete certain tasks such …

    whiterose Repository record for Neural Networks for Control of Artificial Life Form (opens in a new tab)

  5. Growing synfire chains with triphasic spike-time-dependent plasticity

    … reported spike-timing-dependent plasticity (STDP) rule, triphasic STDP, plus activity-dependent excitability. This STDP rule, which has not been previously used in computational studies, is shown to successfully develop a synfire chain in a network of binary neurons. The width and length of …

    whiterose Repository record for Growing synfire chains with triphasic spike-time-dependent plasticity (opens in a new tab)

  6. Constructive spiking neural networks for simulations of neuroplasticity

    … based on spike-timing- dependent plasticity (STDP) that achieves continual one-shot learning of hidden spike patterns through neuron construction. The theoretical developments in this thesis begin with the proposal of a set of definitions of the fundamental components of constructive neural …

    adelaide Repository record for Constructive spiking neural networks for simulations of neuroplasticity (opens in a new tab)

  7. Biologically motivated reinforcement learning in spiking neural networks

    … classical SpikeTime-Dependent Plasticity (STDP) rules and the triplet rules, and rate-based rules such as Oja's Rule and BCM rules, as well as their reward-modulated extensions (such as Reward-Modulated Spike-Time-Dependent Plasticity (R-STDP)), I allow a general biologically feasible …

    cape-town Repository record for Biologically motivated reinforcement learning in spiking neural networks (opens in a new tab)

  8. Inference and Learning in Spiking Neural Networks for Neuromorphic Systems

    … mechanism spike-timing-dependent plasticity (STDP) and its variants are local in synapses and time but are unstable during training and difficult to train multi-layer SNNs.</p><p>To better exploit the energy-saving features such as spike domain representation and stochastic computing provided …

    syracuse-diss Repository record for Inference and Learning in Spiking Neural Networks for Neuromorphic Systems (opens in a new tab)

  9. Inference And Learning In Spiking Neural Networks For Neuromorphic Systems

    … mechanism spike-timing-dependent plasticity (STDP) and its variants are local in synapses and time but are unstable during training and difficult to train multi-layer SNNs.</p><p>To better exploit the energy-saving features such as spike domain representation and stochastic computing provided …

    syracuse-diss Repository record for Inference And Learning In Spiking Neural Networks For Neuromorphic Systems (opens in a new tab)

  10. Shaping of Spike-Timing-Dependent Plasticity curve using interneuron and calcium dynamics

    … of Spike-Timing-Dependent Plasticity (or STDP). Spike-Timing-Dependent Plasticity is the occurrence of either a strengthening or weakening in connection between two neurons, depending on the temporal order of stimulation between them. A major part of the work detailed is the focus on what …

    glasgow Repository record for Shaping of Spike-Timing-Dependent Plasticity curve using interneuron and calcium dynamics (opens in a new tab)

  11. Spike Processing Circuit Design for Neuromorphic Computing

    … design and spike-timing-dependent-plasticity (STDP) based analog design respectively. Both these two ISI encoders have been evaluated through post-layout simulations successfully. The STDP based ISI encoder will be taped out by the end of 2019. A test bench based on correlation inspection has …

    vt Repository record for Spike Processing Circuit Design for Neuromorphic Computing (opens in a new tab)

  12. Induction and Maintenance of Synaptic Plasticity

    … response to spike-timing dependent plasticity (STDP) and presynaptic stimulation protocols. A reduced model based on the CaMKII system is used to elucidate which parameters control the synaptic plasticity outcomes in response to STDP protocols, and in particular how the plasticity results depend …

    qucosa-diss

  13. Strip-till and no-till soybean growth and distribution of roots and soil phosphorus, potassium, and water with broadcast and subsurface-band fertilization

    … dry biomass was consistently higher for STDP than NTBC especially during the late vegetative/early reproductive stage to about R4 development stage. Similarly, STDP produced greater plant height, leaf area index (LAI), and crop growth rate (CGR) compared to NTBC. These findings indicate …

    uiuc Repository record for Strip-till and no-till soybean growth and distribution of roots and soil phosphorus, potassium, and water with broadcast and subsurface-band fertilization (opens in a new tab)

  14. Improving Liquid State Machines Through Iterative Refinement of the Reservoir

    … the liquid with spike-time dependant plasticity (STDP) synapses. Second, we create an eligibility based reinforcement learning algorithm for synaptic development. Third, we apply principles of Hebbian learning and reinforcement learning to create a new algorithm called separation driven synaptic …

    byu Repository record for Improving Liquid State Machines Through Iterative Refinement of the Reservoir (opens in a new tab)

  15. Towards a neocortically-inspired ab initio cellular model of associative memory

    … according to spike-timing dependent plasticity (STDP). We desire to understand how external signals (like speech, vision, etc.) are encoded in the dynamics of such SNNs. In particular, we desire to identify and confirm the extent to which various network-level measurements are …

    uiuc Repository record for Towards a neocortically-inspired ab initio cellular model of associative memory (opens in a new tab)

  16. Ferroelectric doped hafnium oxide and its application on electronic devices

    … also show spike-timing-independent plasticity (STDP) can be obtained in this device, which proves the possibility of using our FTJ as a neuromorphic computing chip.

    uiuc Repository record for Ferroelectric doped hafnium oxide and its application on electronic devices (opens in a new tab)

  17. Pattern Recognition Using Spiking Neural Networks

    … networks using spike time-dependent plasticity (STDP) and assess their performance on real-world machine learning applications like handwritten digit recognition.

    windsor Repository record for Pattern Recognition Using Spiking Neural Networks (opens in a new tab)

  18. Optimizing Reservoir Computing Architecture for Dynamic Spectrum Sensing Applications

    … triplet-based Spike-Timing-Dependent Plasticity (STDP) and various spike encoding schemes on the spectrum dataset within the LSM, we investigate the advantages offered by these proposed techniques compared to traditional LSM models on the FPGA. FPGA boards, known for their power efficiency and low …

    vt Repository record for Optimizing Reservoir Computing Architecture for Dynamic Spectrum Sensing Applications (opens in a new tab)

  19. Investigating neuronal network dynamics : scale-invariance, preferred firing rates, and plasticity via phase-shift encoding

    … stimulations, spike-timing-dependent plasticity (STDP) protocols, and phase-shift encoding experiments, we investigated neuronal network dynamics. Preferred firing rates were identified across multiple neural circuits in an iterative design process, facilitated by Finalspark’s high-resolution, …

    oxford-brookes Repository record for Investigating neuronal network dynamics : scale-invariance, preferred firing rates, and plasticity via phase-shift encoding (opens in a new tab)

  20. Developing digital and analog spiking neural Networks for interacting with biological Tissues in the Case Study of temporal lobe Epilepsy

    … adapt using Spike-Timing-Dependent Plasticity (STDP) algorithms, laying the foundation for further hybrid experiments conducted with the IIT team. Subsequent stages of the project involved the design and fabrication of ASIC chips and PCBs to create a fully custom hardware SNN, culminating in …

    sevilla Repository record for Developing digital and analog spiking neural Networks for interacting with biological Tissues in the Case Study of temporal lobe Epilepsy (opens in a new tab)

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