中国科学院机构知识库网格系统: 检索

TripleBrain: A Compact Neuromorphic Hardware Core With Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity 期刊论文 OAI收割
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2022, 卷号: 16, 期号: 4, 页码: 636-650
作者: Wang, Haibing; He, Zhen; Wang, Tengxiao; He, Junxian; Zhou, Xichuan

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收藏 | 浏览/下载：17/0 | 提交时间：2023/07/12

Neurons Neuromorphics Hardware System-on-chip Field programmable gate arrays Synapses Self-organizing feature maps Neuromorphic system spiking neural network spike-timing dependent plasticity self-organizing map reinforce- ment learning on-chip learning

A Low-Cost FPGA Implementation of Spiking Extreme Learning Machine With On-Chip Reward-Modulated STDP Learning 期刊论文 OAI收割
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2022, 卷号: 69, 期号: 3, 页码: 1657-1661
作者: He, Zhen; Shi, Cong; Wang, Tengxiao; Wang, Ying; Tian, Min

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收藏 | 浏览/下载：44/0 | 提交时间：2022/12/07

Neurons Hardware System-on-chip Costs Training Field programmable gate arrays Computational modeling Neuromorphic computing spiking neural network extreme learning machine spike-timing-dependent plasticity reward-modulated on-chip learning

Stylistic Composition of Melodies Based on a Brain-Inspired Spiking Neural Network 期刊论文 OAI收割
FRONTIERS IN SYSTEMS NEUROSCIENCE, 2021, 卷号: 15, 期号: 0, 页码: 21
作者: Liang, Qian; Zeng, Yi

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收藏 | 浏览/下载：44/0 | 提交时间：2021/04/21

spiking neural network spike-timing dependent plasticity sequential memory musical learning melody composition

Temporal-Sequential Learning With a Brain-Inspired Spiking Neural Network and Its Application to Musical Memory 期刊论文 OAI收割
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2020, 卷号: 14, 页码: 17
作者: Liang, Qian; Zeng, Yi; Xu, Bo

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收藏 | 浏览/下载：19/0 | 提交时间：2020/08/24

spiking neural network sequential memory episodic memory spike-timing-dependent plasticity time perception musical learning

The Central Control System for KTX 期刊论文 OAI收割
IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2018, 卷号: 65, 期号: 8, 页码: 2357-2361
作者: Zhang, Z.; Xiao, B.; Wang, F.; Ji, Z.; Wang, Y.

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收藏 | 浏览/下载：22/0 | 提交时间：2019/11/11

Central control system (CCS) gas injection network reversed field pinch (RFP) safety and interlock timing

Resilience-Aware Frequency Tuning for Neural-Network-Based Approximate Computing Chips 期刊论文 OAI收割
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2017, 卷号: 25, 期号: 10, 页码: 2736-2748
作者: Wang, Ying; Deng, Jiachao; Fang, Yuntan; Li, Huawei; Li, Xiaowei

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收藏 | 浏览/下载：36/0 | 提交时间：2019/12/12

Deep learning error tolerance neural network (NN) timing variation

Time-Frequency System Builds and Timing Strategy Research of VHF Band Antenna Array 会议论文 OAI收割
作者: Liu JQ(刘俊卿); Dong L(董亮); Wang M(汪敏); Guo SJ(郭少杰)

收藏 | 浏览/下载：25/0 | 提交时间：2017/01/03

Antenna Array GPS Network Timing

Different propagation speeds of recalled sequences in plastic spiking neural networks 期刊论文 OAI收割
NEW JOURNAL OF PHYSICS, 2015, 卷号: 17
作者: Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

收藏 | 浏览/下载：24/0 | 提交时间：2016/03/30

sequential activity recall spiking neural network spike-timing dependent plasticity

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

收藏 | 浏览/下载：78/0 | 提交时间：2013/03/25

Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.

improving performance of network covert timing channel through huffman coding 期刊论文 OAI收割
Mathematical and Computer Modelling, 2011, 卷号: 55, 期号: 1-2, 页码: 69-79
Jingzheng Wu; Yongji Wang; Liping Ding; Xiaofeng Liao

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收藏 | 浏览/下载：32/0 | 提交时间：2013/10/08

Huffman coding Network covert channel Covert channel encoding Capacity Covertness Timing channel