作者: gentle 時(shí)間: 2025-3-21 20:59
Norifumi Fujimura,Takeshi Yoshimurade video game and implement a local plasticity rule that enables reinforcement learning, allowing the on-chip neural network to learn to play the game. The experiment demonstrates key aspects of the employed approach, such as accelerated and flexible learning, high energy efficiency and resilience to noise.作者: GRAZE 時(shí)間: 2025-3-22 02:07 作者: Chemotherapy 時(shí)間: 2025-3-22 05:12
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spikinde video game and implement a local plasticity rule that enables reinforcement learning, allowing the on-chip neural network to learn to play the game. The experiment demonstrates key aspects of the employed approach, such as accelerated and flexible learning, high energy efficiency and resilience to noise.作者: 完成才會(huì)征服 時(shí)間: 2025-3-22 09:07 作者: Factual 時(shí)間: 2025-3-22 14:07 作者: JAUNT 時(shí)間: 2025-3-22 17:48
0302-9743 ngs was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.?.978-3-030-30486-7978-3-030-30487-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 最小 時(shí)間: 2025-3-22 22:16 作者: 保留 時(shí)間: 2025-3-23 04:51 作者: gustation 時(shí)間: 2025-3-23 06:28
Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorizationties in time from calcium imaging data. NMF was used because neural activity can be expressed by the sum of individual neuronal activity and fluorescence intensity data are always positive values. We found that there are certain groups of neurons that behave differently between sleep and wake states.作者: integrated 時(shí)間: 2025-3-23 12:12 作者: 膠水 時(shí)間: 2025-3-23 15:30
0302-9743 Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019.?The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learni作者: Peristalsis 時(shí)間: 2025-3-23 18:52 作者: Badger 時(shí)間: 2025-3-23 23:46 作者: 忍受 時(shí)間: 2025-3-24 04:13
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation978-3-030-30487-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: duplicate 時(shí)間: 2025-3-24 08:37
Takeshi Kanashima,Masanori Okuyamaill construct a new and suitable Lyapunov function to derive the sufficient conditions which ensure that the equilibrium point exist and it is globally exponentially stable. A numerical example is given in order to confirm the theoretical developments of this paper.作者: expansive 時(shí)間: 2025-3-24 13:26 作者: 細(xì)查 時(shí)間: 2025-3-24 15:07 作者: 神圣將軍 時(shí)間: 2025-3-24 20:43 作者: calumniate 時(shí)間: 2025-3-25 03:03
Norifumi Fujimura,Takeshi Yoshimuraroach, new sufficient conditions are derived to ensuring the strictly .dissipative of the model. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be easily numerically checked by the MATLAB LMI toolbox. At last, a numerical example with simulation is given to illust作者: 小樣他閑聊 時(shí)間: 2025-3-25 04:00 作者: Engaging 時(shí)間: 2025-3-25 09:22 作者: aggressor 時(shí)間: 2025-3-25 14:42
Takeshi Kanashima,Masanori Okuyamaon the conventional chaotic complex-valued associative memory with adaptive scaling factor that can realize dynamic associations of multi-valued patterns. In the conventional chaotic complex-valued associative memory with adaptive scaling factor, parameters of the chaotic complex-valued neuron model作者: Density 時(shí)間: 2025-3-25 19:36 作者: FUSE 時(shí)間: 2025-3-25 23:11 作者: 火海 時(shí)間: 2025-3-26 01:17 作者: Enrage 時(shí)間: 2025-3-26 04:29
Norifumi Fujimura,Takeshi Yoshimuramorphic computers aim to provide such a substrate that reproduces the brain’s capabilities in terms of adaptive, low-power information processing. We present results from a prototype chip of the BrainScaleS-2 mixed-signal neuromorphic system that adopts a physical-model approach with a 1000-fold acc作者: Infuriate 時(shí)間: 2025-3-26 09:08 作者: Mammal 時(shí)間: 2025-3-26 15:06
Takeshi Kanashima,Masanori Okuyamays a decisive role because of its remarkable flexibility and performance. Recently, a new architecture called Capsule Network (CapsNet) was proposed to improve CNN. Capsule Network is able to preserve more input’s information, especially location information by it’s unique capsule structure and dyna作者: 挑剔為人 時(shí)間: 2025-3-26 20:03 作者: occult 時(shí)間: 2025-3-27 00:57 作者: Deference 時(shí)間: 2025-3-27 04:23
Vladimir Fridkin,Stephen Ducharmend achieves significant increase in performance on some simple datasets like MNIST. However, CapsNet gets a poor performance on more complex datasets like CIFAR-10. To address this problem, we focus on the improvement of the original CapsNet from both the network structure and the dynamic routing me作者: 無(wú)效 時(shí)間: 2025-3-27 08:53
Stability Analysis of a Generalized Class of BAM Neural Networks with Mixed Delaysill construct a new and suitable Lyapunov function to derive the sufficient conditions which ensure that the equilibrium point exist and it is globally exponentially stable. A numerical example is given in order to confirm the theoretical developments of this paper.作者: facilitate 時(shí)間: 2025-3-27 10:47
Detection of Directional Information Flow Induced by TMS Based on Symbolic Transfer Entropy-level studies. Most of previous studies have derived functional or effective connectivity or changes in such connectivity during the resting states or cognitive tasks. However, it is difficult to see how such connectivity derived from “passively” recorded data represent actual neural interactions.作者: 饑荒 時(shí)間: 2025-3-27 13:54
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162647.jpg作者: 易于交談 時(shí)間: 2025-3-27 19:20
https://doi.org/10.1007/978-3-030-30487-4artificial intelligence; classification; clustering; computational linguistics; computer networks; Human-作者: 平項(xiàng)山 時(shí)間: 2025-3-27 22:25
978-3-030-30486-7Springer Nature Switzerland AG 2019作者: Vldl379 時(shí)間: 2025-3-28 04:20
Bidirectional Associative Memory with Block Coding: A Comparison of Iterative Retrieval Methodsde accurate estimates of the maximum pattern number that can be stored at a tolerated noise level of 1%. It is revealed that block coding is most beneficial for sparse activity where each pattern has only . active units.作者: Tortuous 時(shí)間: 2025-3-28 06:15
A Nonlinear Fokker-Planck Description of Continuous Neural Network Dynamicsterizes the model has stationary solutions of the .-MaxEnt type and is associated with a free energy like quantity that decreases during the time-evolution of the system. This framework elucidates a possible dynamical mechanism which can generate .-MaxEnt distributions in Hopfield memory neural netw作者: 愚笨 時(shí)間: 2025-3-28 14:26 作者: 該得 時(shí)間: 2025-3-28 14:35 作者: propose 時(shí)間: 2025-3-28 22:50
A Comparative Analysis of Preprocessing Methods for Single-Trial Event Related Potential Detection framework. Therefore, the three different preprocessing methods could be compared. Also, three different classifiers (i.e., logistic regression (LR), k-nearest neighbors (kNN) and support vector machine (SVM)) were compared as well. In addition, the performance metrics utilized for this purpose wer作者: expound 時(shí)間: 2025-3-29 02:19
Distinguishing Violinists and Pianists Based on Their Brain Signalse best classification performance on 20 seconds EEG segments, but this performance depends on the involved musicians’ expertise. Also, the brain signals of a cellist are demonstrated to be more similar to violinists’ signals than to pianists’ signals. In summary, this paper demonstrates that distinc作者: 合乎習(xí)俗 時(shí)間: 2025-3-29 06:08 作者: arthrodesis 時(shí)間: 2025-3-29 07:25
DDRM-CapsNet: Capsule Network Based on Deep Dynamic Routing Mechanism for Complex Datarify the efficacy of our proposed network on complex data, we conduct experiments with a single model without using any ensembled methods and data augmentation techniques on five real-world complex datasets. The experimental results demonstrate that our proposed method achieves better accuracy resul作者: 種族被根除 時(shí)間: 2025-3-29 12:16
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation28th International C作者: B-cell 時(shí)間: 2025-3-29 18:25 作者: 昆蟲 時(shí)間: 2025-3-29 22:23 作者: 等待 時(shí)間: 2025-3-30 01:46
Norifumi Fujimura,Takeshi Yoshimura in line with a typical multi-modal retrieval system where the entire multi-modal pattern is expected to be retrieved even with a partial query pattern from any of the modalities. We present results related to these two issues on a large database of 7000. captioned-images and establish the practical作者: POINT 時(shí)間: 2025-3-30 08:06
Takeshi Kanashima,Masanori Okuyamaon, it is known that the optimum method of automatically adjusting parameters also differs depending on the value of .. In this study, we also conduct experiments at . and 16, and propose a method to automatically adjust the parameters of the chaotic complex-valued neuron model independently from th作者: 粗鄙的人 時(shí)間: 2025-3-30 10:37 作者: ATP861 時(shí)間: 2025-3-30 15:39 作者: Lumbar-Spine 時(shí)間: 2025-3-30 19:30
Takeshi Kanashima,Masanori Okuyamaalyze effect of CapsNet’s activation function, dimension and application in discriminator. Multiple datasets’ results demonstrate that our model has higher translation quality than convolutional image translation framework.作者: 極深 時(shí)間: 2025-3-30 23:33
Vladimir Fridkin,Stephen Ducharmerify the efficacy of our proposed network on complex data, we conduct experiments with a single model without using any ensembled methods and data augmentation techniques on five real-world complex datasets. The experimental results demonstrate that our proposed method achieves better accuracy resul
