导语

  

内容提要

  

    本书共有六章，分别论述了RFID系统防碰撞基本概念和软件防碰撞、物理防碰撞等技术研究进展、RFID系统物理防碰撞的实验验证系统搭建、RFID系统物理防碰撞的物理学基础、图像学基础、优化算法与RFID系统物理防碰撞、深度学习与RFID系统物理防碰撞。本书章节安排合理，结构清晰，本书主要面向从事物联网和RFID系统设计、开发和检测等行业的专业技术人员和高校光电信息物理、物联网专业的教师和博士生、硕士生、本科生。

1  Overview of RFID system anti-collision technology
  1.1  RFID collision problem and research progress of anti-collision
  1.2  RFID system anti-collision technology
    1.2.1  Information channel and channel capacity
    1.2.2  Software anti-collision
    1.2.3  Physical anti-collision
  1.3  Physical anti-collision
    1.3.1  Definition of physical collision avoidance
    1.3.2  The main features of physical collision avoidance
    1.3.3  The structure of the physical anti-collision system
  References
2  RFID system physical anti-collision experimental verification
  2.1  RFID tag group performance measurement
    2.1.1  Tag group sensitivity
    2.1.2  Measurement system designed
    2.1.3  Single tag sensitivity measurement
    2.1.4  Tag group sensitivity measurement
  2.2  Image feature matching experiment of RFID system physical anti-collision
    2.2.1  Image feature matching based on SIFT algorithm
    2.2.2  Image feature matching based on SURF algorithm
    2.2.3  Image feature matching based on ORB algorithm
    2.2.4  Algorithm comparison results and analysis
    2.2.5  Image feature matching
  2.3  Conclusion
  References
3  Physical theory of RFID system physical anti-collision
  3.1  Thermodynamic analysis of physical anti-collision -Research on the
  effect of temperature on tag performance
    3.1.1  Fundamental principles
    3.1.2  Design of the experimentation system
    3.1.3  Experimental method and result analysis
  3.2  Electromagnetism analysis of physical anti-collision-Research on the
  effect of humidity and salt fog on tag performance
    3.2.1  Effect of humidity on the moving identifying performance of UHF RFID
  System
    3.2.2  Effect of salt mist on the moving identifying performance of UHF RFID
  System
  3.3  Kinetic analysis of physical anti-collision - Fisher information matrix
    3.3.1  Channel model
    3.3.2  Computer simulation and analysis
    3.3.3  Antenna selection techniques
  3.4  Conclusion
  References
4  Image theory of RFID system physical anti-collision
  4.1  Tag distribution based on image matching
    4.1.1  Algorithm design
    4.1.2  Experiment
  4.2  Image processing in multi-tag movement
    4.2.1  Image deblur theory
    4.2.2  Estimation of image blurred angle based on Gabor filter
    4.2.3  Estimation of image blurred length based on generalized regression neural
  network (GRNN)
    4.2.4  De-motion blur analysis and analysis
  4.3  RFID tag positioning method
    4.3.1  mage matching overviev
    4.3.2  Image threshold segmentation technology
    4.3.3  Edge detection algorithm
  4.4  3D space RFID tag location
  4.5  A novel reverse design method of tag antenna based on image analysis
    4.5.1  Introduction
    4.5.2  Design of UHF RFID dipole tag antenna
    4.5.3  UHF RFID tag bend dipole antenna analysis
  4.6  Conclusion
  References
5  Optimization algorithm and RFID system physical anti-collision
  5.1  Physical anti-collision based on Particle Swarm Optimization (PSO)
    5.1.1  Design and application of detection system
    5.1.2  Establishment of 3D tag network based on template matching and edge
  detection
    5.1.3  Prediction of tag distribution based on PSO neural network
  5.2  Physical anti-collision based on Support Vector Machine (SVM)
    5.2.1  RFID detection system
    5.2.2  Position location of tags
    5.2.3  Predict model of RFID tags'distribution based on SVM
  5.3  Physical anti-collision based on Wavelet
    5.3.1  Design of image analysis system
    5.3.2  3D coordinate measurement of RFID tag
    5.3.3  RFID multi-tag wavelet neural network
  5.4  Conclusion
  References
6  Deep learning and RFID system physical anti-collision
  6.1  RFID multi-tag 3D measurement system
    6.1.1  System architecture
    6.1.2  Image process module
  6.2  The theory RFID multi-tag image denoising by FDnCNN
    6.2.1  The proposed FDnCNN network architecture
    6.2.2  Noise level map
    6.2.3  Loss function
    6.2.4  Experimental result and real-time analysis
  6.3  Image motion blur removal
  6.4  Multi-level wavelet-CNN for image restoration in pre-processing
  sub-system
    6.4.1  I mage restoration based on denoising prior
    6.4.2  Half Quadratic Splitting (HQS)
    6.4.3  Method from multi-level WPT to MWCNN
    6.4.4  Network architecture
  6.5  Multi-tag 3D position measurement based on image match
    6.5.1  The image matching method
    6.5.2  RFID tag 2D position measurement
    6.5.3  RFID tag vertical position measurement
  6.6  Nonlinear modeling method based on DBN
    6.6.1  Restricted Boltzmann Machine
    6.6.2  DBN
    6.6.3  RFID tag group model based on DBN
  6.7  Conclusion
  References