文件名称:sons
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Compressive sensing (CS) has been proposed for signals with sparsity
in a linear transform domain. We explore a signal dependent
unknown linear transform, namely the impulse response matrix operating
on a sparse excitation, as in the linear model of speech production,
for recovering compressive sensed speech. Since the linear
transform is signal dependent and unknown, unlike the standard
CS formulation, a codebook of transfer functions is proposed in a
matching pursuit (MP) fr a mework for CS recovery. It is found that
MP is efficient and effective to recover CS encoded speech as well
as jointly estimate the linear model. Moderate number of CS measurements
and low order sparsity estimate will result in MP converge
to the same linear transform as direct VQ of the LP vector derived
the original signal. There is also high positive correlation between
signal domain approximation and CS measurement domain
approximation for a large variety of speech spectra.
in a linear transform domain. We explore a signal dependent
unknown linear transform, namely the impulse response matrix operating
on a sparse excitation, as in the linear model of speech production,
for recovering compressive sensed speech. Since the linear
transform is signal dependent and unknown, unlike the standard
CS formulation, a codebook of transfer functions is proposed in a
matching pursuit (MP) fr a mework for CS recovery. It is found that
MP is efficient and effective to recover CS encoded speech as well
as jointly estimate the linear model. Moderate number of CS measurements
and low order sparsity estimate will result in MP converge
to the same linear transform as direct VQ of the LP vector derived
the original signal. There is also high positive correlation between
signal domain approximation and CS measurement domain
approximation for a large variety of speech spectra.
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下载文件列表
sons\729.wav
....\afblue.wav
....\afdirge.wav
....\al19 (1).wav
....\boing.wav
....\Compressed-Sensing-master\Compressed Sensing\.DS_Store
....\.........................\..................\code\.DS_Store
....\.........................\..................\....\approximate message passing\demo.m
....\.........................\..................\....\...........................\largestElement.m
....\.........................\..................\....\...........................\README.txt
....\.........................\..................\....\...........................\README.txt~
....\.........................\..................\....\...........................\reconstructAmp.m
....\.........................\..................\....\ApproximateMessagePassing.m
....\.........................\..................\....\Bayesian\Experiment_Effect_Undersampling_ratio.m
....\.........................\..................\....\.regman\coordl1breg.m
....\.........................\..................\....\.......\coordl1bregdemo.m
....\.........................\..................\....\.......\coordlsl1.m
....\.........................\..................\....\.......\license.txt
....\.........................\..................\....\.......\readme.txt
....\.........................\..................\....\Camera.tif
....\.........................\..................\....\chaining pursuit\ChainingPursuit.m
....\.........................\..................\....\................\EncodeSignal.m
....\.........................\..................\....\................\example.m
....\.........................\..................\....\................\GenerateMeasurements.m
....\.........................\..................\....\................\readme.rtf
....\.........................\..................\....\Cleves_Corner_Compressed_Sensing.m
....\.........................\..................\....\client.m
....\.........................\..................\....\coordl1breg.m
....\.........................\..................\....\coordl1bregdemo.m
....\.........................\..................\....\coordlsl1.m
....\.........................\..................\....\demo_continuation.m
....\.........................\..................\....\demo_image_deblur.m
....\.........................\..................\....\dtmf.m
....\.........................\..................\....\eta.m
....\.........................\..................\....\etaprime.m
....\.........................\..................\....\failure.m
....\.........................\..................\....\failure.wav
....\.........................\..................\....\fft.mat
....\.........................\..................\....\fftcode.m
....\.........................\..................\....\figures_1_2_3.m
....\.........................\..................\....\figure_4.m
....\.........................\..................\....\figure_5.m
....\.........................\..................\....\figure_6.m
....\.........................\..................\....\FINAL\AMPclient.m
....\.........................\..................\....\.....\AMPserver.m
....\.........................\..................\....\.....\basispursuitclient.m
....\.........................\..................\....\.....\basispursuitserver.m
....\.........................\..................\....\.....\client.m
....\.........................\..................\....\.....\eta.m
....\.........................\..................\....\.....\etaprime.m
....\.........................\..................\....\.....\l1_pd.m
....\.........................\..................\....\.....\largestElement.m
....\.........................\..................\....\.....\OMP.m
....\.........................\..................\....\.....\OMPclient.m
....\.........................\..................\....\.....\OMPserver.m
....\.........................\..................\....\.....\reconstructAmp.m
....\.........................\..................\....\.....\result_graph.m
....\.........................\..................\....\.....\server.m
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