Results 101 to 110 of about 3,974,691 (210)
Siamese neural network architecture for homoglyph attacks detection
ICT Express, 2020 Primarily an adversary uses homoglyph or spoofing attack approach to obfuscate domain name, file name or process names. This approach facilitates to create domain name, file name or process names which look visually homogeneous to legitimate domain name,
Vinayakumar R., Soman K.P.
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Recurrent Neural Networks as Electrical Networks, a Formalization
, 2023 Since the 1980s, and particularly with the Hopfield model, recurrent neural networks or RNN became a topic of great interest. The first works of neural networks consisted of simple systems of a few neurons that were commonly simulated through analogue electronic circuits.
Mariano Caruso, Cecilia Jarne
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ELMAN-RECURRENT NEURAL NETWORK FOR LOAD SHEDDING OPTIMIZATION
Jurnal Ilmiah SINERGI, 2020 Load shedding plays a key part in the avoidance of the power system outage. The frequency and voltage fluidity leads to the spread of a power system into sub-systems and leads to the outage as well as the severe breakdown of the system utility.
Widi Aribowo
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Synchronization of coupled neutral-type neural networks with jumping-mode-dependent discrete and unbounded distributed delays [PDF]
, 2013 This is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 IEEE.In this paper, the synchronization problem is studied for an array of N identical delayed neutral-type neural ...
Liu, Y +11 more
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, 2008 In this paper we demonstrate that signal propagation across a laminar sheet of recurrent neurons is maximised when two conditions are met. First, neurons must be in the so-called centre crossing configuration.
Buckley, Christopher L
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Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization
BioengineeringAccurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right ...
Marcos Aviles +4 more
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Robust Local Cluster Neural Networks (ESANN) [PDF]
, 2006 Eickhoff R, Sitte J, Rückert U. Robust Local Cluster Neural Networks (ESANN). In: Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN).
Eickhoff, Ralf +3 more
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Memristive recurrent neural network
Neurocomputing, 2018 Abstract It is reported a continuous-time neural network in CMOS that uses memristors. These nanodevices are used to achieve some analog functions such as constant current sourcing, decaying term emulation, and resistive connection; all of them representing parameters of the neural network.
Gerardo Marcos Tornez-Xavier +3 more
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Self-Optimization in Continuous-Time Recurrent Neural Networks
Frontiers in Robotics and AI, 2018 A recent advance in complex adaptive systems has revealed a new unsupervised learning technique called self-modeling or self-optimization. Basically, a complex network that can form an associative memory of the state configurations of the attractors on ...
Mario Zarco, Tom Froese, Tom Froese
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A VLSI neuromorphic device for implementing spike-based neural networks [PDF]
, 2011 Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Presented at the Proceedings of the 21st Italian Workshop on Neural Nets (WIRN).We present a neuromorphic VLSI device which comprises hybrid analog/digital ...
Morabito, C. F. +5 more
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