The spatial coding of intensity into neural network

机译：强度进入神经网络的空间编码

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

In this paper the authors describe the coding mode of stimuli intensity into neural network and present two neural networks into opto-electronic technology that codify spatial the input signal intensity. The study utility of mode by coding of intensity into neural network derives from numerous by applications that can have the utilization of coding mode of information. Thus the neural networks presented in this paper have many applications. They can be used into artificial systems that process external or internal stimuli by different intensities achieving decoding of these stimuli, they can be used in the color television, they can be used for neural computers into process by coding of information, etc.

机译：在本文中，作者将刺激强度的编码模式描述为神经网络，并将两个神经网络中的光电技术呈现编码空间输入信号强度的光电技术。通过对神经网络的强度进行编码的研究效用来自可以利用信息编码模式的应用程序源自许多。因此，本文呈现的神经网络具有许多应用。它们可用于通过实现这些刺激解码的不同强度来处理外部或内部刺激的人工系统，它们可以在彩色电视中使用，它们可以通过编码信息来使用神经计算机进程。

著录项

来源
《Conference on Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies》|2007年||共6页
会议地点
作者
Vasile Degeratu; Paul Schiopu; Stefania Degeratu;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类光电子技术的应用;
关键词
neural networks; neural computing; neural computers;

机译：神经网络;神经计算;神经计算机;

相似文献

外文文献
中文文献
专利

1. Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial-temporal features extraction [J] . DAngelo Gianni, Palmieri Francesco Journal of network and computer applications . 2021,第Jana期

机译：网络流量分类使用深卷积复制自动化器神经网络进行空间时间特征提取
2. DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants [J] . Nucleic Acids Research . 2018,第11期

机译：定义：深卷积神经网络精确地量化转录因子-DNA结合的强度，促进功能性非编码变体的评估
3. DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants [J] . Meng Wang, Cheng Tai, Weinan E, Nucleic acids research . 2018,第11期

机译：DeFine：深度卷积神经网络可准确量化转录因子与DNA的结合强度，并有助于评估功能性非编码变体
4. The spatial coding of intensity into neural network [C] . Vasile Degeratu, Paul Schiopu, Stefania Degeratu Conference on Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies . 2007

机译：强度进入神经网络的空间编码
5. Integration of Network Coding, Spatial Diversity and Opportunistic Routing/Forwarding in Wireless Mesh Networks =Integration of Network Coding, Spatial Diversity and Opportunistic Routing/Forwarding in Wireless Mesh Networks [D] . Khan, Mohammad Rizwan. 2017

机译：无线网状网络中网络编码，空间分集和机会路由/转发的集成=无线网状网络中网络编码，空间分集和机会路由/转发的集成
6. DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants [O] . Meng Wang, Cheng Tai, Weinan E, 2018

机译：DeFine：深度卷积神经网络可准确定量转录因子与DNA的结合强度并有助于评估功能性非编码变体
7. DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants [O] . Meng Wang, Cheng Tai, Weinan E, 2018

机译：定义：深卷积神经网络精确地量化转录因子-DNA结合的强度，促进功能性非编码变体的评估

The spatial coding of intensity into neural network

摘要

著录项

相似文献

相关主题

期刊订阅