Reactivating and reorganizing activity-silent working memory: two distinct mechanisms underlying pinging the brain by Yang, C, He, X, Cai, Y

“…Recent studies have proposed that visual information in working memory (WM) can be maintained in an activity-silent state and reactivated by task-irrelevant high-contrast visual impulses (“ping”). Although pinging the brain has become a popular tool for exploring activity-silent WM, its underlying mechanisms remain unclear. …”

Virtual pink dolphins by Lu, Dong Jun.

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Surge in SpikeProp algorithm by Zhang, Zhengyang

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Large-scale tests of hinged slender reinforced concrete columns under eccentric loading by Chuang, Poon Hwei., Kong, Fung Kew.

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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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Isolation and characterisation of Pink Pigmented Facultative Methylotrophs (PPFM) from Malaysian ulam leaves by Ramli, Nur Isti'anah, Abas, Faridah, Ismail, Intan Safinar, Rukayadi, Yaya, Jurime, Nuramiratul Hafizah

“…This study aims to isolate and characterise the Pink Pigmented Facultative Methylotrophs (PPFM) bacteria from the leaves of common Malaysian table salad (ulam). …”
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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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Comparative analysis of dehydration techniques on phytochemical and antibacterial properties on pink and purple flowers impatiens walleriana by Tan, Suat Hian, Sin, Phin Yin, Ros Azlinawati, Ramli, Mohd Hairul, Ab. Rahim, Nyuk, Ling Ma

“…Microwave-dried leaf extracts were evaluated for antibacterial activity using the disc diffusion method. Both pink and purple flower varieties demonstrated inhibition of Gram-positive and Gram-negative bacteria, with the pink flower showing greater antibacterial effects. …”
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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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Bayesian lesion estimation with a structured spike-and-slab prior by Menacher, A, Nichols, T, Holmes, C, Ganjgahi, H

“…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. …”

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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Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

“…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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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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The effect of silver nitrate and silver thiosulphate on in vitro shoot regeneration of australian pink finger lime (Citrus australasica cv. Mia Rose) by Qiao, Stephanie Er Wong, Sreeramanan Subramaniam, Bee, Lynn Chew

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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