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Solving Permutation Switching Problem
of Online ICA
under non-stationary environment
by using Cross-Correlation of Output



                          Yuuki Nakayama, s1130164
                      Supervised by Prof. Shuxue Ding


                 Foundation of Computer Science Laboratory
Outline
•   Independent Component Analysis (ICA)
•   Motivation
•   Method
•   Numeric experiment 1
•   Numeric experiment 2
•   Conclusion
Independent Component Analysis (ICA)

• The technique for separate signals from mixed
  signal
  Drawback : Cannot use real world because of batch processing


                          ↓

  Solution :   online ICA              It can use real time.

  Drawback : causing permutation switching problem
Motivation
• Permutation Switching Problem
   One separated signal may connect to a wrong component signal.




          Separated signal (Permutation Switching happened )


  Solution : Using Cross-Correlation Matrix
Method
• Taking correlations of overlap part between
  two blocks
• Connecting “unmix (signals)” by checking
  correlation values
Numeric experiment 1
  • Stationary Environment
  Original signals             Separated signals             Performance of SIR




Permutation switching problem have been successful solved under stationary environment
Numeric experiment 2
    • Non-stationary Environment (small changing environment)

     Original signals            Separated signals             Performance of SIR




Permutation switching problem have been successful solved under non-stationary environment
Conclusion
• The solving permutation switching problem
  has been successful.



• Future works
  → The algorithm which can separated signals under big changing
    environment is needed

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Thesis Writng Week9

  • 1. Solving Permutation Switching Problem of Online ICA under non-stationary environment by using Cross-Correlation of Output Yuuki Nakayama, s1130164 Supervised by Prof. Shuxue Ding Foundation of Computer Science Laboratory
  • 2. Outline • Independent Component Analysis (ICA) • Motivation • Method • Numeric experiment 1 • Numeric experiment 2 • Conclusion
  • 3. Independent Component Analysis (ICA) • The technique for separate signals from mixed signal Drawback : Cannot use real world because of batch processing ↓ Solution : online ICA It can use real time. Drawback : causing permutation switching problem
  • 4. Motivation • Permutation Switching Problem One separated signal may connect to a wrong component signal. Separated signal (Permutation Switching happened ) Solution : Using Cross-Correlation Matrix
  • 5. Method • Taking correlations of overlap part between two blocks • Connecting “unmix (signals)” by checking correlation values
  • 6. Numeric experiment 1 • Stationary Environment Original signals Separated signals Performance of SIR Permutation switching problem have been successful solved under stationary environment
  • 7. Numeric experiment 2 • Non-stationary Environment (small changing environment) Original signals Separated signals Performance of SIR Permutation switching problem have been successful solved under non-stationary environment
  • 8. Conclusion • The solving permutation switching problem has been successful. • Future works → The algorithm which can separated signals under big changing environment is needed