Earticle

초록

영어

In this paper, we conduct research on issues related to the primary features of the Internet of things system and the corresponding data communication characteristics based on sparse coding and joint deep neural network. Internet of things is more than the underlying device difference communication method and it is the Internet of things needs to study in the field of hot issue. Using traditional algorithm for Internet communication equipment need particle filter was carried out on the acquisition of communication signal processing. Communication technology enables the Internet of things will perceive the information between different terminals for efficient transmission and exchange, exchange and sharing and the information resources is the key to the functions of things. To enhance the robustness and efficiency of the current IOT systems, we adopt the sparse coded dictionary learning theory to detect the size of the data and optimize the compressive sensing technique to modify the resolution. With the advances of the deep neural network, we analyze the topology of the system network structure and extract the pattern features and characteristics to make the signal transmission process more quickly and feasible. To enhance the objective function, we obtain the restricted optimization algorithm to help terminate the iteration for the higher efficiency. In the final part, we simulation our algorithm for times compared with other well-performed approaches. The result indicates that our method outperforms both in the accuracy layer an in the time-consuming layer which will hold specific meaning.

목차

Abstract
 1. Introduction
 2. The Deep Neural Network
  2.1. The General Introduction of the Deep Learning
  2.2. The Theoretical Description of the Deep Neural Network
 3. The Sparse Coding Algorithms and the Dictionary Learning
  3.1. The Introduction to Compressive Sensing
  3.2. The Sparse Coding Algorithms
  3.3. The Dictionary Learning Procedure with OMP
 4. Prior Knowledge based IOT Communication Technique
 5. Numerical Experiment and the Simulation
  5.1. Experimental Environment Initiation
  5.2. Simulation Result and Corresponding Analysis
 6. Conclusion and Summary
 References

키워드

저자

• Jianping PAN [ Technology Department, Taiyuan Satellite Launch Center, Taiyuan, China ]
• Wenzhun HUANG [ Department of Electronic Information Engineering, Xijing University, Xi’an, China ] Corresponding author
• Shanwen ZHANG [ Department of Electronic Information Engineering, Xijing University, Xi’an, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605