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ASPT-2.1 RELEASE NOTES

ASPT-2.1 Release Notes

We are pleased to announce the release of the Adaptive Signal Processing Toolbox Version 2.1 for Matlab (ASPT-2.1). The new release improves and expands the previous ASPT-2.0 release in many fronts. Besides bug fixes, execution speed enhancement for many algorithms, improved and reorganized documentation, the new release adds 15 new adaptive algorithms. The new routines expand the scope of the toolbox to cover nonlinear adaptive filters and add many new high performance adaptive algorithms. The newly added algorithms include routines implementing

  • Fast transversal filters
  • Data reusing filters
  • Block processing filters
  • Recursive least squares filters with error feedback
  • Variable forgetting factor recursive least squares filters
  • Fault tolerant filters
  • Second order Volterra nonlinear filters
For a complete list of the ASPT-2.1 contents, access to the on-line ASPT documentation, available license types, ASPT price list, frequently asked questions, and other ASPT related information, please visit the ASPT for Matlab home page .

The following table lists the contents of ASPT-2.1 release. Algorithms marked with an * after their names have been newly added. The reference page for each of the algorithms can be accessed from the ASPT Quick Reference Guide.

Transversal adaptive filters
asptarlmsnewt - AR modeling implementation of LMS-Newton method.
asptbfdaf - Block Frequency Domain Adaptive Filter.
asptblms * - Block Least Mean Squares and its variants.
asptbnlms * - Block Normalized Least Mean Squares.
asptdrlms * - Data Reusing LMS (DRLMS) and its variants.
asptdrnlms * - Data Reusing Normalized LMS (DRNLMS).
asptftrls * - Fast Transversal RLS Filter.
asptleakynlms - Leaky Normalized Least Mean Squares.
asptlclms - Linearly Constrained LMS.
asptlms - Least Mean Squares (LMS) and its variants.
asptmvsslms - Reduced complexity Variable Step Size LMS.
asptnlms - Normalized LMS.
asptpbfdaf - Partitioned Block Frequency Domain.
asptrcpbfdaf - Reduced Complexity Partitioned Block Frequency Domain.
asptrdrlms * - Recent Data Reusing LMS (DRLMS) and its variants.
asptrdrnlms * - Recent Data Reusing Normalized LMS (DRNLMS).
asptrls - Recursive Least Squares.
aspttdftaf * - Transform Domain Fault Tolerant Adaptive Filter.
aspttdlms - Transform domain LMS.
asptvsslms - Variable Step Size LMS.
asptvffrls * - Variable Forgetting Factor Recursive Least Squares.
init_arlmsnewt - AR modeling implementation of LMS-Newton method.
init_bfdaf - Block Frequency Domain Adaptive Filter.
init_blms * - Block Least Mean Squares and its variants.
init_bnlms * - Block Normalized Least Mean Squares.
init_drlms * - Data Reusing LMS (DRLMS) and its variants.
init_drnlms * - Data Reusing Normalized LMS (DRNLMS).
init_ftrls * - Fast Transversal RLS Filter.
init_leakynlms - Leaky Normalized Least Mean Squares.
init_lclms - Linearly Constrained LMS.
init_lms - Least Mean Squares (LMS) and its variants.
init_mvsslms - Reduced complexity Variable Step Size LMS.
init_nlms - Normalized LMS.
init_pbfdaf - Partitioned Block Frequency Domain.
init_rcpbfdaf - Reduced Complexity Partitioned Block Frequency Domain.
init_rdrlms * - Recent Data Reusing LMS (DRLMS) and its variants.
init_rdrnlms * - Recent Data Reusing Normalized LMS (DRNLMS).
init_rls - Recursive Least Squares.
init_tdftaf * - Transform Domain Fault Tolerant Adaptive Filter.
init_tdlms - Transform domain LMS.
init_vsslms - Variable Step Size LMS.
init_vffrls * - Variable Forgetting Factor Recursive Least Squares.
Lattice adaptive filters
asptftrls * - Fast Transversal RLS Filter.
asptlbpef - Adaptive LMS Lattice Backward Prediction Error Filter.
asptlfpef - Adaptive LMS Lattice Forward Prediction Error Filter.
asptlmslattice - LMS Lattice Joint Process Estimator.
asptrlslbpef - Adaptive RLS Lattice Backward Prediction Error Filter.
asptrlslfpef - Adaptive RLS Lattice Forward Prediction Error Filter.
asptrlslattice - RLS-Lattice joint process estimator using a posteriori estimation errors.
asptrlslattice2 * - RLS-Lattice joint process estimator using a priori estimation errors with error feedback.
init_ftrls * - Fast Transversal RLS Filter.
init_lbpef - Adaptive LMS Lattice Backward Prediction Error Filter.
init_lfpef - Adaptive LMS Lattice Forward Prediction Error Filter.
init_lmslattice - LMS Lattice Joint Process Estimator.
init_rlslbpef - Adaptive RLS Lattice Backward Prediction Error Filter.
init_rlslfpef - Adaptive RLS Lattice Forward Prediction Error Filter.
init_rlslattice - RLS-Lattice joint process estimator using a posteriori estimation errors.
init_rlslattice2 * - RLS-Lattice joint process estimator using a priori estimation errors with error feedback.
Recursive adaptive filters
asptcsoiir2 - Cascaded Second Order IIR adaptive filter.
aspteqerr - Equation Error IIR adaptive filter.
asptouterr - Output Error IIR.
asptsharf - Simple Hyperstable Adaptive Recursive Filter.
asptsoiir1 - Second Order IIR adaptive algorithm type-1.
asptsoiir2 - Second Order IIR adaptive algorithm type-2.
init_csoiir2 - Cascaded Second Order IIR adaptive filter.
init_eqerr - Equation Error IIR adaptive filter.
init_outerr - Output Error IIR.
init_sharf - Simple Hyperstable Adaptive Recursive Filter.
init_soiir1 - Second Order IIR adaptive algorithm type-1.
init_soiir2 - Second Order IIR adaptive algorithm type-2.
Active noise and vibration control filters
asptadjlms - Adjoint LMS.
asptfdadj - Frequency Domain Adjoint LMS.
asptfdfxlms - Frequency Domain Filtered-x LMS.
asptfxlms - Filtered-x LMS.
asptmcadjlms - Multichannel Adjoint LMS.
asptmcfdadjlms - Multichannel Frequency Domain Adjoint LMS.
asptmcfdfxlms - Multichannel Frequency Domain Filtered-x LMS.
asptmcfxlms - Multichannel Filtered-x LMS.
init_adjlms - Adjoint LMS.
init_fdadj - Frequency Domain Adjoint LMS.
init_fdfxlms - Frequency Domain Filtered-x LMS.
init_fxlms - Filtered-x LMS.
init_mcadjlms - Multichannel Adjoint LMS.
init_mcfdadjlms - Multichannel Frequency Domain Adjoint LMS.
init_mcfdfxlms - Multichannel Frequency Domain Filtered-x LMS.
init_mcfxlms - Multichannel Filtered-x LMS.
Non-linear adaptive filters
asptsovlms * - Second order Volterra LMS and its variants.
asptsovnlms * - Second order Volterra Normalized LMS.
asptsovrls * - Second order Volterra RLS.
aspttdlms * - Second order Volterra transform domain LMS.
asptsovvsslms * - Second order Volterra variable step size LMS.
init_sovlms * - Second order Volterra LMS and its variants.
init_sovnlms * - Second order Volterra Normalized LMS.
init_sovrls * - Second order Volterra RLS.
init_tdlms * - Second order Volterra transform domain LMS.
init_sovvsslms * - Second order Volterra variable step size LMS.
Non-adaptive, visualization and helper functions
init_ipwin - Initializes iteration progress GUI window.
ipwin - Builds the iteration progress GUI window.
getStop - Returns the condition of the stop button in the IPWIN.
guifb - Handles the GUI feedback functions of the IPWIN.
mcmixr - Calculates the response of N speakers at M microphones.
osfilter - Fast FIR filtering in frequency domain using overlap-save.
plot_ale - Generates plots for the Adaptive Line Enhancer problems.
plot_anvc - Generates plots for Active Noise and Vibration Control problems.
plot_beam - Generates plots for beam forming problems.
plot_echo - Generates plots for echo cancellers applications.
plot_model - Generates plots for modeling problems.
plot_predict - Generates plots for linear prediction problems.
sovfilt * - Second Order Volterra nonlinear filter.
update_ipwin - Updates the iteration progress GUI window.
Examples and applications
ale_csoiir2 - Adaptive Line Enhancer using CSOIIR2.
ale_soiir1 - Adaptive Line Enhancer using SOIIR1.
ale_soiir2 - Adaptive Line Enhancer using SOIIR2.
anvc_adjlms - Active noise and vibration control using ADJLMS.
anvc_fdadjlms - Active noise and vibration control using FDADJLMS.
anvc_fdfxlms - Active noise and vibration control using FDFXLMS.
anvc_fxlms - Active noise and vibration control using FXLMS.
anvc_mcadjlms - Active noise and vibration control using MCADJLMS.
anvc_mcfdadjlms - Active noise and vibration control using MCFDADJLMS.
anvc_mcfdfxlms - Active noise and vibration control using MCFDFXLMS.
anvc_mcfxlms - Active noise and vibration control using MCFXLMS.
beambb_lclms - Beam former at base-band frequency using LCLMS.
beambb_lms - Beam former at base-band frequency using LMS.
beamrf_lms - Beam former at RF frequency using LMS.
echo_bfdaf - Echo canceller using BFDAF.
echo_leakynlms - Echo canceller using LEAKYNLMS.
echo_nlms - Echo canceller using NLMS.
echo_pbfdaf - Echo canceller using PBFDAF.
echo_rcpbfdaf - Echo canceller using RCPBFDAF.
equalizer_nlms - Inverse modeling using NLMS.
equalizer_rls - Inverse modeling using RLS.
model_arlmsnewt - Modeling using LMS-NEWTON.
model_eqerr - IIR modeling using EQER.
model_lmslattice - Modeling using LMSLATTICE.
model_mvsslms - FIR modeling using MVSSLMS.
model_outerr - IIR modeling using OUTERR.
model_rls - FIR modeling using RLS.
model_rlslattice - Modeling using RLSLATTICE.
model_sharf - IIR modeling using SHARF.
model_tdlms - FIR modeling using TRANSFORMLMS.
model_vsslms - FIR modeling using VSSLMS.
predict_lbpef - lattice prediction using LBPEF.
predict_lfpef - lattice prediction using LFPEF.
predict_rlslbpef - lattice prediction using RLSLBPEF.
predict_rlslfpef - lattice prediction using RLSLFPEF.
Test and examples Scripts
testarlmsnewt - Example using AR modeling implementation of LMS-Newton method.
testbfdaf - Example using Block Frequency Domain Adaptive Filter.
testblms * - Example using Block LMS filter.
testbnlms * - Example using Block Normalized LMS filter.
testdrlms * - Example using Data Reusing LMS filter.
testdrnlms * - Example using Data Reusing Normalized LMS filter.
testftrls * - Example using Fast Transversal RLS Filter.
testleakynlms - Example using Leaky Normalized LMS filter.
testlclms - Example using Linearly Constrained LMS filter.
testlms - Example using Least Mean Squares filter.
testmvsslms - Example using Reduced complexity Variable Step Size LMS filter.
testnlms - Example using Normalized LMS filter.
testpbfdaf - Example using Partitioned Block Frequency Domain filter.
testrcpbfdaf - Example using Reduced Complexity Partitioned BFDAF.
testrdrlms * - Example using Recent Data Reusing LMS filter.
testrdrnlms * - Example using Recent Data Reusing Normalized LMS filter.
testrls - Example using Recursive Least Squares filter.
testtdftaf * - Example using Transform Domain Fault Tolerant Adaptive Filter.
testtdlms - Example using Transform domain LMS filter.
testvsslms - Example using Variable Step Size LMS filter.
testvffrls * - Example using Variable Forgetting Factor RLS filter.
testlbpef - Example using Adaptive LMS Lattice Backward Prediction Error Filter.
testlfpef - Example using Adaptive LMS Lattice Forward Prediction Error Filter.
testlmslattice - Example using LMS Lattice Joint Process Estimator filter.
testrlslbpef - Example using Adaptive RLS Lattice Backward Prediction Error Filter.
testrlslfpef - Example using Adaptive RLS Lattice Forward Prediction Error Filter.
testrlslattice - Example using RLS-Lattice joint process estimator using a posteriori estimation errors.
testrlslattice2 * - Example using RLS-Lattice joint process estimator using a priori estimation errors with error feedback.
testcsoiir2 - Example using Cascaded Second Order IIR adaptive filter.
testeqerr - Example using Equation Error IIR adaptive filter.
testouterr - Example using Output Error IIR filter.
testsharf - Example using Simple Hyperstable Adaptive Recursive Filter.
testsoiir1 - Example using Second Order IIR adaptive filter type-1.
testsoiir2 - Example using Second Order IIR adaptive filter type-2.
testadjlms - Example using Adjoint LMS controller.
testfdadj - Example using Frequency Domain Adjoint LMS controller.
testfdfxlms - Example using Frequency Domain Filtered-x LMS controller.
testfxlms - Example using Filtered-x LMS controller.
testmcadjlms - Example using Multichannel Adjoint LMS controller.
testmcfdadjlms - Example using Multichannel Frequency Domain Adjoint LMS controller.
testmcfdfxlms - Example using Multichannel Frequency Domain Filtered-x LMS controller.
testmcfxlms - Example using Multichannel Filtered-x LMS controller.
testsovlms * - Example using Second order Volterra LMS filter.
testsovnlms * - Example using Second order Volterra Normalized LMS filter.
testsovrls * - Example using Second order Volterra RLS filter.
testtdlms * - Example using Second order Volterra transform domain LMS filter.
testsovvsslms * - Example using Second order Volterra variable step size LMS filter.
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