pack_sobi_instantaneous_cp3
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(ack sobi_cp3
Second Order Blind Identification via Candecomp/Parafac order-3 (CP3)
to solve linear instantaneous Blind Source Separation (BSS).
sobi_cp3 allows to handle the exactly-determined, the over-determined and
several under-determined problems.
sobi_cp3 computes a set of K covariance matrices of the observed signals.
Then, the mixing matrix is estimated by joint-approximate-diagonalization (JAD)
of this set of matrices.
The JAD problem is solved by computing the CP3 decomposition of the third-order
tensor (3-way array) built by stacking the covariance matrices along the third
dimension.
It exploits the fact that JAD is a particular case of CP3 where the slices of
the tensor are symmetric, i.e., the mode-1 and mode-2 loading matrices
of the decomposition are identical.
Here the cp3 model is fitted by ignoring this symmetry, via an alternating
least squares (ALS) coupled with exact line search.
Thanks to powerful uniqueness properties of CP3, estimation of t)
文件列表:
pack_sobi_instantaneous_cp3 (0, 2010-10-08)
pack_sobi_instantaneous_cp3\speech (0, 2010-10-08)
pack_sobi_instantaneous_cp3\bss_algos (0, 2010-10-08)
pack_sobi_instantaneous_cp3\solve_perm_scale.m (3637, 2010-10-08)
pack_sobi_instantaneous_cp3\generate_source.m (1608, 2010-10-08)
pack_sobi_instantaneous_cp3\demo2.m (4308, 2010-10-08)
pack_sobi_instantaneous_cp3\demo1.m (3737, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\sentence_male_29s.wav (928044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\sentence_female_28s.wav (896044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\numbers_female_29s.wav (928044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\Music_trumpet_30s.wav (960044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\Music_piano_30s.wav (960044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\Iam_female_30s.wav (960044, 2010-10-08)
pack_sobi_instantaneous_cp3\speech\henry_theater_male_30s.wav (960044, 2010-10-08)
pack_sobi_instantaneous_cp3\bss_algos\sobi_cp3.m (42001, 2010-10-08)
pack_sobi_instantaneous_cp3\bss_algos\jadeR.m (11337, 2010-10-08)
Pack sobi_cp3
Second Order Blind Identification via Candecomp/Parafac order-3 (CP3)
to solve linear instantaneous Blind Source Separation (BSS).
sobi_cp3 allows to handle the exactly-determined, the over-determined and
several under-determined problems.
sobi_cp3 computes a set of K covariance matrices of the observed signals.
Then, the mixing matrix is estimated by joint-approximate-diagonalization (JAD)
of this set of matrices.
The JAD problem is solved by computing the CP3 decomposition of the third-order
tensor (3-way array) built by stacking the covariance matrices along the third
dimension.
It exploits the fact that JAD is a particular case of CP3 where the slices of
the tensor are symmetric, i.e., the mode-1 and mode-2 loading matrices
of the decomposition are identical.
Here the cp3 model is fitted by ignoring this symmetry, via an alternating
least squares (ALS) coupled with exact line search.
Thanks to powerful uniqueness properties of CP3, estimation of the mixing
matrix is still possible in several under-determined cases (more sources
than sensors), which is a powerful feature, compared to classical sobi-based
BSS algorithms.
@Copyright July 2010
Dimitri Nion (feedback: dimitri.nion@gmail.com)
For non-commercial use only
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