Добірка наукової літератури з теми "Neuroinspired"

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Статті в журналах з теми "Neuroinspired":

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Chen, Pai-Yu, and Shimeng Yu. "Technological Benchmark of Analog Synaptic Devices for Neuroinspired Architectures." IEEE Design & Test 36, no. 3 (June 2019): 31–38. http://dx.doi.org/10.1109/mdat.2018.2890229.

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Alibart, Fabien, Stéphane Pleutin, Olivier Bichler, Christian Gamrat, Teresa Serrano-Gotarredona, Bernabe Linares-Barranco, and Dominique Vuillaume. "A Memristive Nanoparticle/Organic Hybrid Synapstor for Neuroinspired Computing." Advanced Functional Materials 22, no. 3 (December 2011): 609–16. http://dx.doi.org/10.1002/adfm.201101935.

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Bogdanov, Andrey V. "Neuroinspired Architecture for Robust Classifier Fusion of Multisensor Imagery." IEEE Transactions on Geoscience and Remote Sensing 46, no. 5 (May 2008): 1467–87. http://dx.doi.org/10.1109/tgrs.2008.916214.

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4

Yan, Xiaobing, Jianhui Zhao, Sen Liu, Zhenyu Zhou, Qi Liu, Jingsheng Chen, and Xiang Yang Liu. "Memristor with Ag-Cluster-Doped TiO2Films as Artificial Synapse for Neuroinspired Computing." Advanced Functional Materials 28, no. 1 (November 2017): 1705320. http://dx.doi.org/10.1002/adfm.201705320.

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Zhao, Mengliu, Yong Sun, Lei Yan, Zhen Zhao, Linxia Wang, Xiaobing Yan, and Kaiyou Wang. "Memristor with BiVO4 nanoparticle as artificial synapse for neuroinspired computing." Applied Physics Letters 120, no. 9 (February 2022): 093501. http://dx.doi.org/10.1063/5.0079418.

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A memristor is very important for the development of an artificial neuromorphic system. However, the breakthrough of the limit of a work region for memristors remains challenging. Herein, a BiVO4 nanoparticle is proposed to be a high-performance artificial synapse for a neuromorphic system. A BiVO4-based artificial synapse exhibits superior bidirectional analog switching properties. Furthermore, the fundamental neurobiological synaptic functions in the BiVO4-based artificial synapse can be achieved, such as potentiation, a depression, nonlinear transmission, spike-time-dependent plasticity, pair-pulse facilitation, and the transition from short-term to long-term potentiation. Moreover, the movement of oxygen vacancies by an electric field is responsible for resistance switching. This work provides different insights into the design of an artificial synapse based on memristors.
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Zhao, Jianhui, Zhenyu Zhou, Yuanyuan Zhang, Jingjuan Wang, Lei Zhang, Xiaoyan Li, Mengliu Zhao, et al. "An electronic synapse memristor device with conductance linearity using quantized conduction for neuroinspired computing." Journal of Materials Chemistry C 7, no. 5 (2019): 1298–306. http://dx.doi.org/10.1039/c8tc04395g.

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An electrochemical metallization memristor based on Zr0.5Hf0.5O2 film and an active Cu electrode with quantum conductance and neuromorphic behavior has been reported in this work.
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Sun, Lin, Yi Du, Haiyang Yu, Huanhuan Wei, Wenlong Xu, and Wentao Xu. "An Artificial Reflex Arc That Perceives Afferent Visual and Tactile Information and Controls Efferent Muscular Actions." Research 2022 (February 2022): 1–11. http://dx.doi.org/10.34133/2022/9851843.

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Neural perception and action-inspired electronics is becoming important for interactive human-machine interfaces and intelligent robots. A system that implements neuromorphic environmental information coding, synaptic signal processing, and motion control is desired. We report a neuroinspired artificial reflex arc that possesses visual and somatosensory dual afferent nerve paths and an efferent nerve path to control artificial muscles. A self-powered photoelectric synapse between the afferent and efferent nerves was used as the key information processor. The artificial reflex arc successfully responds to external visual and tactile information and controls the actions of artificial muscle in response to these external stimuli and thus emulates reflex activities through a full reflex arc. The visual and somatosensory information is encoded as impulse spikes, the frequency of which exhibited a sublinear dependence on the obstacle proximity or pressure stimuli. The artificial reflex arc suggests a promising strategy toward developing soft neurorobotic systems and prostheses.
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Mofrad, Asieh Abolpour, Matthew G. Parker, Zahra Ferdosi, and Mohammad H. Tadayon. "Clique-Based Neural Associative Memories with Local Coding and Precoding." Neural Computation 28, no. 8 (August 2016): 1553–73. http://dx.doi.org/10.1162/neco_a_00856.

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Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.
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Yan, Xiaobing, Jianhui Zhao, Sen Liu, Zhenyu Zhou, Qi Liu, Jingsheng Chen, and Xiang Yang Liu. "Memristors: Memristor with Ag-Cluster-Doped TiO2 Films as Artificial Synapse for Neuroinspired Computing (Adv. Funct. Mater. 1/2018)." Advanced Functional Materials 28, no. 1 (January 2018): 1870002. http://dx.doi.org/10.1002/adfm.201870002.

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Ellenbogen, JR, V. Narbad, H. Hasegawa, and R. Selway. "P32 Targeting accuracy of the neuromate robot in DBS implantation for paediatric dystonia." Journal of Neurology, Neurosurgery & Psychiatry 90, no. 3 (February 2019): e33.2-e33. http://dx.doi.org/10.1136/jnnp-2019-abn.105.

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ObjectivesTo quantify the accuracy of DBS electrode implantation for movement disorder in paediatric patients utilising the neuroinspire™ software and neuromate® robot.DesignRetrospective, single-centre, cohort study.SubjectsFifteen patients with dystonia (67% female; median age 11 years, range 8–18 years) underwent intervention since May 2017.MethodsDBS procedures were planned on the neuroinspire™ software and electrodes were implanted using the Renishaw neuromate® robot and Renishaw guide tubes and secured with a dog-bone plate under general anaesthetic. Post-operative CT imaging with the intra-operative O-arm was fused to pre-operative imaging. Planned entry and target coordinates were compared to actual entry and final target coordinates in order to obtain absolute and directional errors in x (medial-lateral), y (anterior-posterior) and z (dorsal-ventral) planes. Euclidean error was calculated for each electrode. Wilcoxon signed-rank test was used to analyse error.ResultsBilateral GPi were targeted and Medtronic DBS systems were implanted for each patient (n=30). Overall median Euclidean error for electrode implantation was 2.13 mm (range, 0.71–4.85; p<0.001). No discrepancy between left- and right-sided electrodes was seen (p=0.346). Absolute errors in x (med 1.25 mm, range 0.10–4.10), y (med 0.80 mm, range 0–2.70) and z (med 1.45 mm, range 0–3.90) planes were individually significant (p<0.001). On overall anterior displacement of leads was observed (med 0.55+0.85 mm, p=0.001) but there was no significant directional bias in x (p=0.219) or z (p=0.077) planes.ConclusionsWe observed an improvement in the discrepancy seen between planned and actual lead location compared to a previously reported series using the Leksell frame in a similar cohort. Addressing possible compounding factors such as drilling techniques and electrode fixation should increase accuracy further. The neuromate® Robot is a reliable and accurate alternative to the Leksell frame.

Дисертації з теми "Neuroinspired":

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Henniquau, Dimitri. "Conception d’une interface fonctionnelle permettant la communication de neurones artificiels et biologiques pour des applications dans le domaine des neurosciences." Electronic Thesis or Diss., Université de Lille (2018-2021), 2021. http://www.theses.fr/2021LILUN032.

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L’ingénierie neuromorphique est un nouveau champ disciplinaire en plein essor qui fait appel à des compétences en électronique, mathématiques, informatique et en ingénierie biomorphique dans le but de produire des réseaux de neurones artificiels capables de traiter les informations à la manière du cerveau humain. Ainsi, les systèmes neuromorphiques offrent non seulement des solutions plus performantes et efficientes que les technologies actuelles de traitement de l’information mais permettent également d’envisager le développement de stratégies thérapeutiques inédites dans le cadre de dysfonctionnements cérébraux pathologiques. Le groupe Circuits Systèmes Applications des Micro-ondes (CSAM) de l’Institut d’Electronique, de Microélectronique et de Nanotechnologies (IEMN) dans lequel ces travaux de thèse ont été effectués a contribué à l’émergence de ces systèmes neuromorphiques en développant une boîte à outils complète de neurones et synapses artificiels. Pour intégrer l’ingénierie neuromorphique dans la prise en charge de dysfonctionnements neuronaux pathologiques, il convient d’interfacer les neurones artificiels et les neurones vivants afin d’assurer une communication réelle entre ces différents composants. Dans ce contexte, et en utilisant les outils innovants développés par le groupe CSAM, l’objectif de ce travail de thèse a été de concevoir et réaliser une interface fonctionnelle permettant d’établir une boucle de communication bidirectionnelle entre des neurones artificiels et des neurones vivants. Les neurones artificiels développés par le groupe CSAM sont réalisés en technologie CMOS et capables d’émettre des signaux électriques biomimétiques. Les neurones vivants sont issus de cellules PC12 différenciées. Une première étape de ce travail a consisté à modéliser et à simuler cette interface entre neurones artificiels et vivants ; une deuxième partie de la thèse a été dédiée à la fabrication et à la caractérisation d’interfaces neurobiohybrides, ainsi qu’à la croissance et à la caractérisation de neurones vivants, avant d’étudier leur capacité à communiquer avec des neurones artificiels. Ainsi, un modèle de membrane neuronale représentant un neurone vivant interfacé avec une électrode métallique planaire a été développé. L’exploitation de ce modèle a permis de montrer qu’il est possible de stimuler des neurones vivants en utilisant les signaux biomimétiques issus du modèle de neurones artificiels tout en conservant des tensions d’excitation faibles. L’utilisation de faibles tensions d’excitation permettrait d’améliorer l’efficacité énergétique des systèmes neurobiohybrides intégrant des neurones artificiels et d’amoindrir le risque d’endommager les tissus vivants. Ensuite, le neurobiohybride permettant d’interfacer les neurones vivants et les neurones artificiels a été conçu et réalisé. Une caractérisation expérimentale de cette interface a permis de valider l’approche consistant à exciter un neurone vivant au travers d’une électrode métallique planaire. Enfin, des cellules neuronales vivantes issues de cellules PC-12 ont été cultivées et différenciées dans les neurobiohybrides. Une preuve expérimentale de la capacité des signaux électriques biomimétiques produits par les neurones artificiels a ainsi pu être apportée par la technique d’imagerie calcique. En conclusion, les travaux présentés dans ce manuscrit établissent clairement la preuve de concept de l’excitation de neurones vivants par un signal biomimétique dans nos conditions expérimentales et étayent ainsi la première partie de la boucle de communication bidirectionnelle entre neurones artificiels et neurones vivants
Neuromorphic engineering is an exciting emerging new field, which combines skills in electronics, mathematics, computer sciences and biomorphic engineering with the aim of developing artificial neuronal networks capable of reproducing the brain’s data processing. Thus, neuromorphic systems not only offer more effective and energy efficient solutions than current data processing technologies, but also set the bases for developing novel original therapeutic strategies in the context of pathological brain dysfunctions. The research group Circuits Systèmes Applications des Micro-ondes (CSAM) of the Institute for Electronics, Microelectronics and Nanotechnologies (IEMN) in Lille, in which this thesis work was carried out, has contributed to the generation of such neuromorphic systems by developing a toolbox constituted of artificial neurons and synapses. In order to implement neuromorphic engineering in the therapeutic arsenal for treating neurologic disorders, we need to interface living and artificial neurons to ensure real communication between these different components. In this context and using the original tools developed by the CSAM group, the main goal of this thesis work was to design and produce a functional interface allowing a bidirectional communication loop to be established between living and artificial neurons. These artificial neurons have been developed by the CSAM group using CMOS technology and are able to emit biomimetic electrical signals. Living neurons were obtained from differentiated PC-12 cells. A first step in this work consisted in modeling and simulating this interface between artificial and living neurons; a second part of the thesis was dedicated to the fabrication and characterization of neurobiohybrid interfaces, and to the growth and characterization of living neurons before studying their capacities to communicate with artificial neurons. First, a model of neuronal membrane representing a living neuron interfaced with a metallic planar electrode has been developed. We thus showed that it is possible to excite neurons using biomimetic signals produced by artificial neurons while maintaining a low excitation voltage. Low voltage excitation would improve energy efficiency of neurobiohybrid systems integrating artificial neurons and reduce the impact of harmful electrical signals on living neurons. Then, the neurobiohybrid interfacing living and artificial neurons has been designed and produced. The results obtained by experimental characterization of this interface validate the approach consisting in exciting living neurons through a metallic planar electrode. Finally, living neurons from PC-12 cells were grown and differentiated directly onto neurobiohybrids. Then, an experimental proof of the ability of biomimetic electrical signals to excite living neurons was obtained using calcium imaging. To conclude, the work presented in this manuscript clearly establishes a proof of concept for the excitation of living neurons using a biomimetic signal in our experimental conditions and thus substantiates the first part of the bidirectional communication loop between artificial neurons and living neurons
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Williame, Jérôme. "Oscillateurs nanomagnétiques soumis à une boucle de rétroaction à retard : Bruit, chaos et applications neuromorphiques." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS119.

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Une boucle de rétroaction à retard a lieu lorsque la sortie d’un système est utilisée pour modifier le signal d’entrée de ce dernier. Ce phénomène apparaît dans des domaines aussi variés que la physique des amplificateurs, la biologie de la régulation de l’insuline ou encore les sciences sociales. Les effets d’une boucle de rétroaction à retard sur un système électronique sont bien connus et ont donné lieu à de nombreuses applications : boucle à verrouillage de phase pour améliorer les propriétés stochastiques, boucle d’amplification ou de régulation, etc. Cependant ces effets ont étés relativement peu étudiés dans le cadre des systèmes nanomagnétiques. Dans ces travaux de thèse j'ai étudié théoriquement les conséquences d'une boucle de rétroaction à retard sur la dynamique de l'aimantation de trois différents systèmes nanométriques avec un objectif distinct pour chaque système. Le premier concerne un oscillateur à transfert de spin dont j’ai étudié les propriétés stochastiques. La rétroaction engendre de fortes variations de la largeur spectrale et fait apparaitre de bandes secondaires à larges retards. Le deuxième système étudié est l'oscillateur macrospin dans lequel des transitions chaotiques entre deux modes de précession (dans le plan de la couche et hors du plan) sont induites par la rétroaction. Je montre qu'il est possible d'exploiter de telle dynamique pour la génération de nombres aléatoires. Enfin le troisième système représente une implémentation d'un oscillateur du type « Mackey-Glass » avec une paroi de domaine piégée dans un ruban. En déformant cette paroi par courant polarisé de spin, et avec un choix judicieux du signal de sortie, je démontre que ce système peut servir comme élément de base pour une architecture temporelle d'un calculateur avec réservoir (« reservoir computer »), qui permet d'effectuer des tâches comme la prédiction des séries temporelles non linéaires
A delay feedback loop occurs when the output of a system is used to modify the input signal of the system. This phenomenon appears in fields as varied as the physics of amplifiers, the biology of insulin regulation or in social interactions. The effects of a delay feedback loop on an electronic system are well known and have given rise to many applications: phase-locked loops to improve stochastic properties, amplification or regulation loops, and so on. However, these feedback effects remain relatively unexplored in the context of nanomagnetic systems. In this thesis I have studied theoretically the consequences of delayed feedback on the magnetization dynamics of three different nanoscale systems with a separate focus for each system. The first involves spin-torque nano-oscillators whose stochastic properties and the impact of a feedback loop on them have been studied. It is found that significant changes can occur to the spectral linewidth, along with the appearance of secondary frequencies at large delays. The second system involves the macrospin oscillator, where I investigated how delayed feedback can induce chaotic transitions between the in-plane and out-ofplane precession states. These complex dynamics can be used to generate random numbers. The third system represents a proposal for implementing a Mackey-Glass oscillator using a domain wall racetrack-like geometry. By deforming this domain wall with spin polarized currents and with a suitable readout function, I show that this oscillator can be used for a time-delay architecture for reservoir computing. Tests of nonlinear time series prediction are conducted to evaluate the performance of this system

Тези доповідей конференцій з теми "Neuroinspired":

1

Locatelli, Nicolas, Julie Grollier, Damien Querlioz, Adrien F. Vincent, Alice Mizrahi, Joseph S. Friedman, Damir Vodenicarevic, Joo-Von Kim, Jacques-Olivier Klein, and Weisheng Zhao. "Spintronic Devices as Key Elements for Energy-Efficient Neuroinspired Architectures." In Design, Automation and Test in Europe. New Jersey: IEEE Conference Publications, 2015. http://dx.doi.org/10.7873/date.2015.1117.

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Beck, Cornelia, Umberto Olcese, Alberto Montagner, Stefan Ringbauer, Heiko Neumann, Antonio Frisoli, Rita Almeida, Massimo Bergamasco, and Gustavo Deco. "A neuroinspired cognitive behavioral control architecture for visually driven mobile robotics." In 2008 IEEE International Conference on Robotics and Biomimetics. IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.4913342.

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