Artigos de revistas sobre o tema "Spiking neural works"
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Ponghiran, Wachirawit, e Kaushik Roy. "Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junho de 2022): 8001–8. http://dx.doi.org/10.1609/aaai.v36i7.20771.
Texto completo da fonteChunduri, Raghavendra K., e Darshika G. Perera. "Neuromorphic Sentiment Analysis Using Spiking Neural Networks". Sensors 23, n.º 18 (6 de setembro de 2023): 7701. http://dx.doi.org/10.3390/s23187701.
Texto completo da fonteSzczęsny, Szymon, Damian Huderek e Łukasz Przyborowski. "Spiking Neural Network with Linear Computational Complexity for Waveform Analysis in Amperometry". Sensors 21, n.º 9 (10 de maio de 2021): 3276. http://dx.doi.org/10.3390/s21093276.
Texto completo da fonteNgu, Huynh Cong Viet, e Keon Myung Lee. "Effective Conversion of a Convolutional Neural Network into a Spiking Neural Network for Image Recognition Tasks". Applied Sciences 12, n.º 11 (6 de junho de 2022): 5749. http://dx.doi.org/10.3390/app12115749.
Texto completo da fonteNgu, Huynh Cong Viet, e Keon Myung Lee. "Effective Conversion of a Convolutional Neural Network into a Spiking Neural Network for Image Recognition Tasks". Applied Sciences 12, n.º 11 (6 de junho de 2022): 5749. http://dx.doi.org/10.3390/app12115749.
Texto completo da fonteYan, Zhanglu, Jun Zhou e Weng-Fai Wong. "Near Lossless Transfer Learning for Spiking Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de maio de 2021): 10577–84. http://dx.doi.org/10.1609/aaai.v35i12.17265.
Texto completo da fonteKim, Youngeun, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Anna Hambitzer e Priyadarshini Panda. "Exploring Temporal Information Dynamics in Spiking Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 7 (26 de junho de 2023): 8308–16. http://dx.doi.org/10.1609/aaai.v37i7.26002.
Texto completo da fonteMárquez-Vera, Carlos Antonio, Zaineb Yakoub, Marco Antonio Márquez Vera e Alfian Ma'arif. "Spiking PID Control Applied in the Van de Vusse Reaction". International Journal of Robotics and Control Systems 1, n.º 4 (25 de novembro de 2021): 488–500. http://dx.doi.org/10.31763/ijrcs.v1i4.490.
Texto completo da fonteWu, Yujie, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie e Luping Shi. "Direct Training for Spiking Neural Networks: Faster, Larger, Better". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 1311–18. http://dx.doi.org/10.1609/aaai.v33i01.33011311.
Texto completo da fonteLourenço, J., Q. R. Al-Taai, A. Al-Khalidi, E. Wasige e J. Figueiredo. "Resonant Tunnelling Diode – Photodetectors for spiking neural networks". Journal of Physics: Conference Series 2407, n.º 1 (1 de dezembro de 2022): 012047. http://dx.doi.org/10.1088/1742-6596/2407/1/012047.
Texto completo da fonteFu, Si-Yao, Guo-Sheng Yang e Xin-Kai Kuai. "A Spiking Neural Network Based Cortex-Like Mechanism and Application to Facial Expression Recognition". Computational Intelligence and Neuroscience 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/946589.
Texto completo da fonteXiao, Chao, Jihua Chen e Lei Wang. "Optimal Mapping of Spiking Neural Network to Neuromorphic Hardware for Edge-AI". Sensors 22, n.º 19 (24 de setembro de 2022): 7248. http://dx.doi.org/10.3390/s22197248.
Texto completo da fonte‘Atyka Nor Rashid, Fadilla, e Nor Surayahani Suriani. "Spiking neural network classification for spike train analysis of physiotherapy movements". Bulletin of Electrical Engineering and Informatics 9, n.º 1 (1 de fevereiro de 2020): 319–25. http://dx.doi.org/10.11591/eei.v9i1.1868.
Texto completo da fonteKheradpisheh, Saeed Reza, e Timothée Masquelier. "Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron". International Journal of Neural Systems 30, n.º 06 (28 de maio de 2020): 2050027. http://dx.doi.org/10.1142/s0129065720500276.
Texto completo da fonteAl-Hamid, Ali A., e HyungWon Kim. "Optimization of Spiking Neural Networks Based on Binary Streamed Rate Coding". Electronics 9, n.º 10 (29 de setembro de 2020): 1599. http://dx.doi.org/10.3390/electronics9101599.
Texto completo da fonteQin, Xing, Chaojie Li, Haitao He, Zejun Pan e Chenxiao Lai. "Python-Based Circuit Design for Fundamental Building Blocks of Spiking Neural Network". Electronics 12, n.º 11 (23 de maio de 2023): 2351. http://dx.doi.org/10.3390/electronics12112351.
Texto completo da fonteKorsakov, Anton, Lyubov Astapova e Aleksandr Bakhshiev. "Application of a Compartmental Spiking Neuron Model with Structural Adaptation for Solving Classification Problems". Informatics and Automation 21, n.º 3 (13 de maio de 2022): 493–520. http://dx.doi.org/10.15622/ia.21.3.2.
Texto completo da fonteQiu, Xuerui, Rui-Jie Zhu, Yuhong Chou, Zhaorui Wang, Liang-Jian Deng e Guoqi Li. "Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 1 (24 de março de 2024): 601–10. http://dx.doi.org/10.1609/aaai.v38i1.27816.
Texto completo da fonteSakthivadivel, Dalton A. R. "Formalizing the Use of the Activation Function in Neural Inference". Complex Systems 31, n.º 4 (15 de dezembro de 2022): 433–49. http://dx.doi.org/10.25088/complexsystems.31.4.433.
Texto completo da fonteLiu, Jing, Xu Yang, Yimeng Zhu, Yunlin Lei, Jian Cai, Miao Wang, Ziyi Huan e Xialv Lin. "How Neuronal Noises Influence the Spiking Neural Networks’s Cognitive Learning Process: A Preliminary Study". Brain Sciences 11, n.º 2 (25 de janeiro de 2021): 153. http://dx.doi.org/10.3390/brainsci11020153.
Texto completo da fonteKanazawa, Yusuke, Tetsuya Asai e Yoshihito Amemiya. "Basic Circuit Design of a Neural Processor: Analog CMOS Implementation of Spiking Neurons and Dynamic Synapses". Journal of Robotics and Mechatronics 15, n.º 2 (20 de abril de 2003): 208–18. http://dx.doi.org/10.20965/jrm.2003.p0208.
Texto completo da fonteHandy, Gregory, e Alla Borisyuk. "Investigating the ability of astrocytes to drive neural network synchrony". PLOS Computational Biology 19, n.º 8 (9 de agosto de 2023): e1011290. http://dx.doi.org/10.1371/journal.pcbi.1011290.
Texto completo da fonteSaemaldahr, Raghdah, e Mohammad Ilyas. "Patient-Specific Preictal Pattern-Aware Epileptic Seizure Prediction with Federated Learning". Sensors 23, n.º 14 (21 de julho de 2023): 6578. http://dx.doi.org/10.3390/s23146578.
Texto completo da fonteO’Donnell, Cian, J. Tiago Gonçalves, Nick Whiteley, Carlos Portera-Cailliau e Terrence J. Sejnowski. "The Population Tracking Model: A Simple, Scalable Statistical Model for Neural Population Data". Neural Computation 29, n.º 1 (janeiro de 2017): 50–93. http://dx.doi.org/10.1162/neco_a_00910.
Texto completo da fonteWang, Jiang, Ruixue Han, Xilei Wei, Yingmei Qin, Haitao Yu e Bin Deng. "Weak signal detection and propagation in diluted feed-forward neural network with recurrent excitation and inhibition". International Journal of Modern Physics B 30, n.º 02 (20 de janeiro de 2016): 1550253. http://dx.doi.org/10.1142/s0217979215502537.
Texto completo da fonteLi, Duowei, Jianping Wu e Depin Peng. "Online Traffic Accident Spatial-Temporal Post-Impact Prediction Model on Highways Based on Spiking Neural Networks". Journal of Advanced Transportation 2021 (2 de dezembro de 2021): 1–20. http://dx.doi.org/10.1155/2021/9290921.
Texto completo da fonteHarel, Yuval, e Ron Meir. "Optimal Multivariate Tuning with Neuron-Level and Population-Level Energy Constraints". Neural Computation 32, n.º 4 (abril de 2020): 794–828. http://dx.doi.org/10.1162/neco_a_01267.
Texto completo da fonteKleijnen, Robert, Markus Robens, Michael Schiek e Stefan van Waasen. "A Network Simulator for the Estimation of Bandwidth Load and Latency Created by Heterogeneous Spiking Neural Networks on Neuromorphic Computing Communication Networks". Journal of Low Power Electronics and Applications 12, n.º 2 (21 de abril de 2022): 23. http://dx.doi.org/10.3390/jlpea12020023.
Texto completo da fonteWang, Yihao, Danqing Wu, Yu Wang, Xianwu Hu, Zizhao Ma, Jiayun Feng e Yufeng Xie. "A Low-Cost Hardware-Friendly Spiking Neural Network Based on Binary MRAM Synapses, Accelerated Using In-Memory Computing". Electronics 10, n.º 19 (8 de outubro de 2021): 2441. http://dx.doi.org/10.3390/electronics10192441.
Texto completo da fonteChen, Ruizhi, e Ling Li. "Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation". Neural Computation 32, n.º 12 (dezembro de 2020): 2557–600. http://dx.doi.org/10.1162/neco_a_01319.
Texto completo da fonteQiu, Xiaorong, Ye Xu, Yingzhong Shi, S. Kannadhasan Deepa e S. Balakumar. "Maximum Entropy Principle Based on Bank Customer Account Validation Using the Spark Method". Journal of Computer Networks and Communications 2023 (31 de dezembro de 2023): 1–13. http://dx.doi.org/10.1155/2023/8840168.
Texto completo da fonteMorita, Kenta, Haruhiko Takase, Naoki Morita, Hiroharu Kawanak e Hidehiko Kita. "Spiking Neural Network to Extract Frequent Words from Japanese Speech Data". Procedia Computer Science 159 (2019): 363–71. http://dx.doi.org/10.1016/j.procs.2019.09.191.
Texto completo da fonteFadhil, Muthna Jasim, Maitham Ali Naji e Ghalib Ahmed Salman. "Transceiver error reduction by design prototype system based on neural network analysis method". Indonesian Journal of Electrical Engineering and Computer Science 18, n.º 3 (1 de junho de 2020): 1244. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1244-1251.
Texto completo da fonteNaudin, Loïs. "Biological emergent properties in non-spiking neural networks". AIMS Mathematics 7, n.º 10 (2022): 19415–39. http://dx.doi.org/10.3934/math.20221066.
Texto completo da fonteGrimaldi, Antoine, Amélie Gruel, Camille Besnainou, Jean-Nicolas Jérémie, Jean Martinet e Laurent U. Perrinet. "Precise Spiking Motifs in Neurobiological and Neuromorphic Data". Brain Sciences 13, n.º 1 (29 de dezembro de 2022): 68. http://dx.doi.org/10.3390/brainsci13010068.
Texto completo da fonteLong, Yun. "Design and Evaluation of English Vocabulary Learning Aids Based on Word Vector Modelling". Journal of Electrical Systems 20, n.º 6s (29 de abril de 2024): 1763–74. http://dx.doi.org/10.52783/jes.3094.
Texto completo da fonteHayat, Hanna, Amit Marmelshtein, Aaron J. Krom, Yaniv Sela, Ariel Tankus, Ido Strauss, Firas Fahoum, Itzhak Fried e Yuval Nir. "Reduced neural feedback signaling despite robust neuron and gamma auditory responses during human sleep". Nature Neuroscience 25, n.º 7 (julho de 2022): 935–43. http://dx.doi.org/10.1038/s41593-022-01107-4.
Texto completo da fontePattusamy, Murugan, e Lakshmi Kanth. "Classification of Tweets Into Facts and Opinions Using Recurrent Neural Networks". International Journal of Technology and Human Interaction 19, n.º 1 (10 de março de 2023): 1–14. http://dx.doi.org/10.4018/ijthi.319358.
Texto completo da fonteHatsopoulos, N. G., M. Burrows e G. Laurent. "Hysteresis reduction in proprioception using presynaptic shunting inhibition". Journal of Neurophysiology 73, n.º 3 (1 de março de 1995): 1031–42. http://dx.doi.org/10.1152/jn.1995.73.3.1031.
Texto completo da fonteLarsson, J. P., Fátima Vera Constán, Núria Sebastián-Gallés e Gustavo Deco. "Lexical Plasticity in Early Bilinguals Does Not Alter Phoneme Categories: I. Neurodynamical Modeling". Journal of Cognitive Neuroscience 20, n.º 1 (janeiro de 2008): 76–94. http://dx.doi.org/10.1162/jocn.2008.20004.
Texto completo da fonteSkinner, T. L., e B. Peretz. "Age sensitivity of osmoregulation and of its neural correlates in Aplysia". American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 256, n.º 4 (1 de abril de 1989): R989—R996. http://dx.doi.org/10.1152/ajpregu.1989.256.4.r989.
Texto completo da fonteWoo, Dae-Seong, Hyun-Do Choi, Hong-Uk Jin, Jae-Kyeong Kim, Tae-Hun Shim e Jea-Gun Park. "Multi-Bit Self-Rectifying Synaptic Memristor Having Tri-Layer Structure for Quantization Aware Training of Quantized Neural Network". ECS Meeting Abstracts MA2023-02, n.º 30 (22 de dezembro de 2023): 1560. http://dx.doi.org/10.1149/ma2023-02301560mtgabs.
Texto completo da fonteLee, Albert K., e Matthew A. Wilson. "A Combinatorial Method for Analyzing Sequential Firing Patterns Involving an Arbitrary Number of Neurons Based on Relative Time Order". Journal of Neurophysiology 92, n.º 4 (outubro de 2004): 2555–73. http://dx.doi.org/10.1152/jn.01030.2003.
Texto completo da fonteUusitalo, R. O., M. Juusola e M. Weckstrom. "Graded responses and spiking properties of identified first-order visual interneurons of the fly compound eye". Journal of Neurophysiology 73, n.º 5 (1 de maio de 1995): 1782–92. http://dx.doi.org/10.1152/jn.1995.73.5.1782.
Texto completo da fonteBarrio, L. C., A. Araque e W. Buno. "Participation of voltage-gated conductances on the response succeeding inhibitory synaptic potentials in the crayfish slowly adapting stretch receptor neuron". Journal of Neurophysiology 72, n.º 3 (1 de setembro de 1994): 1140–51. http://dx.doi.org/10.1152/jn.1994.72.3.1140.
Texto completo da fonteYan, Yulong, Haoming Chu, Yi Jin, Yuxiang Huan, Zhuo Zou e Lirong Zheng. "Backpropagation With Sparsity Regularization for Spiking Neural Network Learning". Frontiers in Neuroscience 16 (14 de abril de 2022). http://dx.doi.org/10.3389/fnins.2022.760298.
Texto completo da fonteGuo, Yufei, Xuhui Huang e Zhe Ma. "Direct learning-based deep spiking neural networks: a review". Frontiers in Neuroscience 17 (16 de junho de 2023). http://dx.doi.org/10.3389/fnins.2023.1209795.
Texto completo da fontePoliti, Antonio, e Alessandro Torcini. "A robust balancing mechanism for spiking neural networks". Chaos: An Interdisciplinary Journal of Nonlinear Science 34, n.º 4 (1 de abril de 2024). http://dx.doi.org/10.1063/5.0199298.
Texto completo da fonteWang, Jing. "Training multi-layer spiking neural networks with plastic synaptic weights and delays". Frontiers in Neuroscience 17 (24 de janeiro de 2024). http://dx.doi.org/10.3389/fnins.2023.1253830.
Texto completo da fontePandey, Shagun. "Advancements in Gas Recognition Techniques for Electronic Nose Systems: A Comparative Review of Classical Methods and Spiking Neural Networks". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, n.º 07 (22 de julho de 2023). http://dx.doi.org/10.55041/ijsrem24791.
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