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7 Summary of adaptive applications

Table 3.12 lists the simulation scripts of adaptive applications included in the current release of the Adaptive Signal Processing Toolbox, with a short description of each script, and a pointer to the application reference section.



Table 3.12: Adaptive filters applications.


Script Name Reference Short Description
ale_ csoiir2 10.1 Adaptive Line Enhancer using CSOIIR2.
ale_ soiir1 10.2 Adaptive Line Enhancer using SOIIR1.
ale_ soiir2 10.3 Adaptive Line Enhancer using SOIIR2.
anvc_ adjlms 10.4 Active noise and vibration control using ADJLMS.
anvc_ fdadjlms 10.5 Active noise and vibration control using FDADJLMS.
anvc_ fdfxlms 10.6 Active noise and vibration control using FDFXLMS.
anvc_ fxlms 10.7 Active noise and vibration control using FXLMS.
anvc_ mcadjlms 10.8 Active noise and vibration control using MCADJLMS.
anvc_ mcfdadjlms 10.9 Active noise and vibration control using MCFDADJLMS.
anvc_ mcfdfxlms 10.10 Active noise and vibration control using MCFDFXLMS.
anvc_ mcfxlms 10.11 Active noise and vibration control using MCFXLMS.
beambb_ lclms 10.12 Beam former at base-band frequency using LCLMS.
beamrf_ lms 10.13 Beam former at RF frequency using LMS.
echo_ bfdaf 10.14 Echo canceler using BFDAF.
echo_ leakynlms 10.15 Echo canceler using LEAKYNLMS.
echo_ nlms 10.16 Echo canceler using NLMS.
echo_ pbfdaf 10.17 Echo canceler using PBFDAF.
echo_ rcpbfdaf 10.18 Echo canceler using RCPBFDAF.
equalizer_ nlms 10.19 Inverse modeling using NLMS.
equalizer_ rls 10.20 Inverse modeling using RLS.
model_ arlmsnewt 10.21 Modeling using LMS-NEWTON.
model_ eqerr 10.22 IIR modeling using EQERR.
model_ lmslattice 10.23 Modeling using LMSLATTICE.
model_ mvsslms 10.24 FIR modeling using MVSSLMS.
model_ outerr 10.25 IIR modeling using OUTERR.
model_ rlslattice 10.26 Modeling using RLSLATTICE.
model_ sharf 10.27 IIR modeling using SHARF.
model_ tdlms 10.28 FIR modeling using TDLMS.
model_ vsslms 10.29 FIR modeling using VSSLMS.
predict_ lbpef 10.30 Prediction using LBPEF.
predict_ lfpef 10.31 Prediction using LFPEF.
predict_ rlslbpef 10.32 Prediction using RLSLBPEF.
predict_ rlslfpef 10.33 Prediction using RLSLFPEF.



next up previous contents
Next: 4 Transversal and Linear Up: 3 ASPT Quick Reference Previous: 6 Summary of Non-adaptive,   Contents