Sparse Dynamic Binary Neural Networks for Storage and Switching of Binary Periodic Orbits

机译：稀疏动态二进制神经网络，用于存储和交换二进制周期轨道

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

A sparse dynamic binary neural network is characterized by local binary connection and can exhibit various binary periodic orbits. First, we consider a condition of sparse connection parameters that guarantees storage and switching of binary periodic orbits. Second, we give two examples of the network that realize the storage and stitching of two periodic orbits related to insect gaits patterns. Presenting an FPGA-based hardware, typical phenomena are confirmed experimentally.

机译：稀疏动态二进制神经网络的特征在于局部二进制连接，并且可以表现出各种二进制周期轨道。首先，我们考虑稀疏连接参数的条件，该条件保证了二进制周期轨道的存储和切换。其次，我们给出网络的两个示例，这些示例实现了与昆虫步态模式相关的两个周期性轨道的存储和缝合。展示基于FPGA的硬件，典型现象已通过实验得到证实。

著录项

来源
《International conference on neural information processing;Annual conference of Asia-Pacific Neural Network Society》|2019年|536-542|共7页
会议地点
作者
Shota Anzai; Seitaro Koyama; Shunsuke Aoki; Toshirnichi Saito;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类
关键词
Binary neural networks; Periodic orbits; Stability;

机译：二进制神经网络周期性轨道;稳定性;

相似文献

外文文献
中文文献
专利

1. Guaranteed storage and stabilization of desired binary periodic orbits in three-layer dynamic binary neural networks [J] . Koyama Seitaro, Saito Toshimichi Neurocomputing . 2020,第Nova27期

机译：在三层动态二元神经网络中保证储存和稳定期望的二元周期轨道
2. Stabilization of desired periodic orbits in dynamic binary neural networks [J] . Sato Ryuji, Saito Toshimichi Neurocomputing . 2017,第JULa26期

机译：动态二元神经网络中所需周期轨道的稳定
3. A Cascade System of Dynamic Binary Neural Networks and Learning of Periodic Orbit [J] . Jungo MORIYASU, Toshimichi SAITO IEICE transactions on information and systems . 2015,第9期

机译：动态二进制神经网络的级联系统和周期轨道的学习
4. Sparse Dynamic Binary Neural Networks for Storage and Switching of Binary Periodic Orbits [C] . Shota Anzai, Seitaro Koyama, Shunsuke Aoki, International Conference on Neural Information Processing . 2019

机译：用于存储和切换二进制周期轨道的稀疏动态二进制神经网络
5. Programmable Manycore Accelerator for Machine Learning, Convolution Neural Network and Binary Neural Network [D] . Kulkarni, Adwaya Amey. 2017

机译：面向机器学习，卷积神经网络和二进制神经网络的可编程Manycore加速器
6. Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods [O] . Holger Höfling, Robert Tibshirani -1

机译：使用伪似然估计稀疏二进制成对马尔可夫网络的估计
7. SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A Novel Approach To Train Convolutional Neural Networks On Lung CT Scans Using Binary Labels Only [O] . M. Zusag, S. R. Desai, M. Di Paolo, 2019

机译：SAPSAM - 稀疏地注释的病理符号激活地图 - 一种使用二元标签培训肺CT扫描上的卷积神经网络的新方法
8. Dynamic Attractors and Basin Class Capacity in Binary Neural Networks. [R] . Dayhoff, J. E., Palmadesso, P. J. 1994

机译：二元神经网络中的动态吸引子和盆地类能力。

Sparse Dynamic Binary Neural Networks for Storage and Switching of Binary Periodic Orbits

摘要

著录项

相似文献

相关主题

期刊订阅