Showing 1 - 20 results of 114 for search '"(tim OR time) (spicer" OR (spice" OR spike"))', query time: 0.11s Refine Results
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    Robustness to training disturbances in SpikeProp Learning by Shrestha, Sumit Bam, Song, Qing

    Published 2020
    “…Stability is a key issue during spiking neural network training using SpikeProp. The inherent nonlinearity of Spiking Neuron means that the learning manifold changes abruptly; therefore, we need to carefully choose the learning steps at every instance. …”
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    Journal Article
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    Impact of spike anneal on ultra shallow junction formation by Lai, Chung Woh

    Published 2008
    “…This report explains the need for ultra shallow junctions for modern day CMOS devices, how spike anneal can help achieve this, reviews the important parameters if this process and how these parameters affect the performances of the CMOS transistors.…”
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    Thesis
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    Automated spike detection using cascade of simple classifiers by Guo, Jingyao

    Published 2016
    “…The infinite variety of spike morphologies and the similarity of spikes to normal EEG and artifacts also make the detection of spikes difficult. …”
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    Thesis
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    Designing a spiking neural network system for object recognition by Thong, Jing Yuan

    Published 2022
    “…Widely touted as the 3rd generation of neural networks, Spiking Neural Networks were introduced as an enhanced representation of working memory. …”
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    Final Year Project (FYP)
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    Dissipative solitons with extreme spikes in the normal and anomalous dispersion regimes by Akhmediev, N., Soto-Crespo, J. M., Vouzas, Peter, Devine, N., Chang, Wonkeun

    Published 2022
    “…In this paper, one recent example is considered—dissipative solitons with extreme spikes (DSESs). It was found that DSESs exist in large regions of the parameter space of the complex cubic–quintic Ginzburg–Landau equation. …”
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    Journal Article
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    Bayesian lesion estimation with a structured spike-and-slab prior by Menacher, A, Nichols, T, Holmes, C, Ganjgahi, H

    Published 2024
    “…Our method also accounts for underestimation of posterior variance due to variational inference by providing an approximate posterior sampling approach based on Bayesian bootstrap ideas and spike-and-slab priors with random shrinkage targets. …”
    Journal article
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    FPGA implementation of spiking convolutional neural networks for voice keyword recognition by Ng, Wei Soon

    Published 2021
    “…The spiking convolutional neural network (SCNN) is a hybrid model of both the spiking neural network (SNN) and convolutional neural network (CNN). …”
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    Final Year Project (FYP)
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    Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

    Published 2014
    “…Bio-inspired, cortex-like, spikebased features are obtained through event-driven convolution and neural competition. The extracted spike feature patterns are then classified by a network of leaky integrate-and-fire (LIF) spiking neurons, in which the weights are trained using tempotron learning rule. …”
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    Conference Paper
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    Morphological learning in spiking neurons: a new hardware efficient maching learning method by Jahagirdar, Kavya

    Published 2014
    “…The latest developments in the research of spiking neural network models have shown that unlike the classic neural network models, these models communicate via precisely timed neuron spikes, thus making them a closer representation of the biological neurons. …”
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    Final Year Project (FYP)
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    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

    Published 2017
    “…This study proposes sequence learning for the fish motion trajectory by using the Spike-Time dependent Plasticity (STDP) in the Spiking Neural Networks (SNNs). …”
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    Monograph
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    EEG data handling using AWS cloud computing for automatic spike detection in epilepsy patients by Rajput Kalpana Bharatsingh

    Published 2017
    “…In this work, we explore the feasibility of AWS-cloud based approach for handling large EEG data for automatic spike detection in epilepsy patients. The aim is to design a system which will allow neurologists to upload and download EEG data from any region for analysis purpose; in the future the data will be analysed by machine learning algorithms. …”
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    Thesis
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    Event-driven spiking neural networks using asynchronous-logic network-on-chip routers in field programmable gate array (FPGA) by Wu, Si

    Published 2023
    “…Compared with the second-generation neural network, SNN uses spikes to process information. The neuronal units in SNNs are only active when they receive or emit spikes, so it is event-driven, thus making it energy-efficient. …”
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    Thesis-Master by Coursework
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    Dok3 restrains neutrophil production of calprotectin during TLR4 sensing of SARS-CoV-2 spike protein by Loh, Jia Tong, Teo, Joey Kay Hui, Lam, Kong-Peng

    Published 2023
    “…In this study, we showed that Dok3 adaptor restrains calprotectin production by neutrophils in response to SARS-CoV-2 spike (S) protein engagement of TLR4. Dok3 recruits SHP-2 to mediate the de-phosphorylation of MyD88 at Y257, thereby attenuating downstream JAK2-STAT3 signaling and calprotectin production. …”
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    Journal Article