Surge in SpikeProp algorithm by Zhang, Zhengyang

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Identification and application of self-binding zipper-like sequences in SARS-CoV spike protein by Zhang, Si Min, Liao, Ying, Neo, Tuan Ling, Lu, Yanning, Liu, Ding Xiang, Vahlne, Anders, Tam, James Pingkwan

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A spiking neural network for pattern recognition by Nurin Atikah Bohari

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Robustness to training disturbances in SpikeProp Learning by Shrestha, Sumit Bam, Song, Qing

“…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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Impact of spike anneal on ultra shallow junction formation by Lai, Chung Woh

“…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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Automated spike detection using cascade of simple classifiers by Guo, Jingyao

“…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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Bayesian lesion estimation with a structured spike-and-slab prior by Menacher, A, Nichols, T, Holmes, C, Ganjgahi, H

“…The use of mean-field variational inference with dynamic posterior exploration, which is an annealing-like strategy that improves optimization, allows our method to scale to large sample sizes. …”

Designing a spiking neural network system for object recognition by Thong, Jing Yuan

“…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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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

“…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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Zeolitic imidazolate frameworks activate endosomal Toll-like receptors and potentiate immunogenicity of SARS-CoV-2 spike protein trimer by Alsaiari, Shahad K., Nadeef, Seba, Daristotle, John L., Rothwell, William, Du, Bujie, Garcia, Johnny, Zhang, Linzixuan, Sarmadi, Morteza, Forster, Timothy A., Menon, Nandita, Lin, Stacey Qiaohui, Tostanoski, Lisa H., Hachmann, Nicole, Wang, Erika Yan, Ventura, John D., Barouch, Dan H., Langer, Robert, Jaklenec, Ana

“…In this work, we report the Toll-like receptor agonist activity of a nanoscale adjuvant zeolitic imidazolate framework–8 (ZIF-8). …”
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FPGA implementation of spiking convolutional neural networks for voice keyword recognition by Ng, Wei Soon

“…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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Stronger dielectric-elastomer grippers using spine-like bending structure by Heng, Kim Rui

“…The gripper is developed based on a new design of DEA using stiffer spine-like structure made of 380μm thick Polyvinyl chloride (PVC) sheet. …”
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Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

“…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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Morphological learning in spiking neurons: a new hardware efficient maching learning method by Jahagirdar, Kavya

“…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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Design of a hybrid neural spike detection algorithm for implantable integrated brain circuits by Zeinolabedin, Seyed Mohammad Ali, Do, Anh Tuan, Yeo, Kiat Seng, Kim, Tony Tae-Hyoung

Subjects: “…Spike…”
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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

“…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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Virus-like particles of nodavirus displaying the receptor binding domain of SARS-CoV-2 spike protein: a potential VLP-based COVID-19 vaccine by Kumar, Kiven, Tan, Wen Siang, Arshad, Siti Suri, Ho, Kok Lian

“…The receptor binding domain (RBD) of the virus spike (S) glycoprotein has been extensively used in vaccine development due to its role in host cell attachment and penetration. …”
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Parameter optimization of evolving spiking neural networks using improved firefly algorithm for classification tasks / by Farezdzuan Roslan, 1992-, author 616568, Haza Nuzly Abdull Hamed, supervisor 308916, Fakulti Kejuruteraan. Sekolah Komputeran 619086

Parameter optimization of evolving spiking neural networks using improved firefly algorithm for classification tasks / by Farezdzuan Roslan, 1992-, author 616568

EEG data handling using AWS cloud computing for automatic spike detection in epilepsy patients by Rajput Kalpana Bharatsingh

“…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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