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Wyświetlanie 1-10 z 72
Tytuł:
Pattern classification by spiking neural networks combining self-organized and reward-related spike-timing-dependent plasticity
Autorzy:
Nobukawa, Sou
Nishimura, Haruhiko
Yamanishi, Teruya
Powiązania:
https://bibliotekanauki.pl/articles/91886.pdf
Data publikacji:
2019
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
spiking neural network
spike timing-dependent plasticity
dopamine-modulated spike timing-dependent plasticity
pattern classification
Opis:
Many recent studies have applied to spike neural networks with spike-timing-dependent plasticity (STDP) to machine learning problems. The learning abilities of dopaminemodulated STDP (DA-STDP) for reward-related synaptic plasticity have also been gathering attention. Following these studies, we hypothesize that a network structure combining self-organized STDP and reward-related DA-STDP can solve the machine learning problem of pattern classification. Therefore, we studied the ability of a network in which recurrent spiking neural networks are combined with STDP for non-supervised learning, with an output layer joined by DA-STDP for supervised learning, to perform pattern classification. We confirmed that this network could perform pattern classification using the STDP effect for emphasizing features of the input spike pattern and DA-STDP supervised learning. Therefore, our proposed spiking neural network may prove to be a useful approach for machine learning problems.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 4; 283-291
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Creation through Polychronization
Autorzy:
Matthias, John
Powiązania:
https://bibliotekanauki.pl/articles/632533.pdf
Data publikacji:
2017
Wydawca:
Projekt Avant
Tematy:
collaboration
composition
polychronization
spike timing dependent plasticity
Opis:
I have recently suggested that some of the processes involved in the collaborative composition of new music could be analogous to several ideas introduced by Izhikevich in his theory of cortical spiking neurons and simple memory, a process which he calls Polychronization. In the Izhikevich model, the evocation of simple memories is achieved by the sequential re-firing of the same Polychronous group of neurons which was initially created in the cerebral cortex by the sensual stimulus. Each firing event within the group is contingent upon the previous firing event and, in particular, contingent upon the timing of the firings, due to a phenomenon known as “Spike Timing Dependent Plasticity.” I argue in this article that the collaborative creation of new music involves contingencies which form a Polychronous group across space and time which helps to create a temporary shared memorial space between the collaborators.
Źródło:
Avant; 2017, 8
2082-6710
Pojawia się w:
Avant
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Kernel analysis for estimating the connectivity of a network with event sequences
Autorzy:
Tezuka, T.
Claramunt, C.
Powiązania:
https://bibliotekanauki.pl/articles/91880.pdf
Data publikacji:
2017
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
connectivity estimation
neural network
kernel methods
spike train
Opis:
Estimating the connectivity of a network from events observed at each node has many applications. One prominent example is found in neuroscience, where spike trains (sequences of action potentials) are observed at each neuron, but the way in which these neurons are connected is unknown. This paper introduces a novel method for estimating connections between nodes using a similarity measure between sequences of event times. Specifically, a normalized positive definite kernel defined on spike trains was used. The proposed method was evaluated using synthetic and real data, by comparing with methods using transfer entropy and the Victor-Purpura distance. Synthetic data was generated using CERM (Coupled Escape-Rate Model), a model that generates various spike trains. Real data recorded from the visual cortex of an anaesthetized cat was analyzed as well. The results showed that the proposed method provides an effective way of estimating the connectivity of a network when the time sequences of events are the only available information.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2017, 7, 1; 17-31
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Libańska lekcja
Autorzy:
Matuszak, Jacek Zygmunt (1976- ).
Szydlik, Cezary.
Powiązania:
Wojska Lądowe 2006, nr 21, s. 8
Data publikacji:
2006
Tematy:
Spike (pocisk rakietowy) użycie Izrael
Spike (pocisk rakietowy) obsługa i eksploatacja szkolenie
II wojna libańska (2006)
Pociski przeciwpancerne kierowane użycie Izrael
Opis:
Zawiera wypow.: kpt. Cezarego Szydlika z Centrum Szkolenia Artylerii i Uzbrojenia w Toruniu.
Fot.
Dostawca treści:
Bibliografia CBW
Artykuł
Wyświetlanie 1-10 z 72

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