I was able to extract the sliding wavelet denoising kernel by injecting an
impulse to the entire DWT-noise elimination-IDWT process. The impulse
response in time-domain is in fact the kernel I want. And, the kernel can
represent the entire denoising process. So, the problem is resolved. The
case now is closed.
-poj
>I think packing all DWT-noise elimination-IDWT into a single sliding
kernel
>is the best idea. Does anyone know how to do it?
>
>Happy New Year!
>
>
>
>
>>On Dec 27, 3:16 pm, "Poj" <netsir...@hotmail.com> wrote:
>>> Hi John,
>>>
>>> Thanks for message.
>>>
>>> Yes, you are right. Lag between input and output is too much. Do you
>have
>>> any articles, links or other information related to sliding DWT?
>>>
>>
>>
>>I only have what can be found with a search on IEEE Xplore or Google
>>Scholar.
>>
>>John
>>
>
Reply by Poj●December 31, 20072007-12-31
I think packing all DWT-noise elimination-IDWT into a single sliding kernel
is the best idea. Does anyone know how to do it?
Happy New Year!
>On Dec 27, 3:16 pm, "Poj" <netsir...@hotmail.com> wrote:
>> Hi John,
>>
>> Thanks for message.
>>
>> Yes, you are right. Lag between input and output is too much. Do you
have
>> any articles, links or other information related to sliding DWT?
>>
>
>
>I only have what can be found with a search on IEEE Xplore or Google
>Scholar.
>
>John
>
Reply by Randy Yates●December 28, 20072007-12-28
John <sampson164@gmail.com> writes:
> On Dec 27, 7:17 pm, Randy Yates <ya...@ieee.org> wrote:
>> John <sampson...@gmail.com> writes:
>> > On Dec 27, 5:56 pm, Jerry Avins <j...@ieee.org> wrote:
>> >> John wrote:
>> >> > On Dec 27, 12:59 pm, Vladimir Vassilevsky <antispam_bo...@hotmail.com>
>> >> > wrote:
>> >> >>>> If you are using a linear filter to resolve the frequencies, then the
>> >> >>>> incurred delay can't be less then about 1/transition band.
>> >> >>> Baseline wander removal is difficult in a realtime system for all the
>> >> >>> reasons you cite.
>> >> >> The only way to trick the nature is using parametric models of the
>> >> >> signal and the drift. The parameters should be estimated as ML. However
>> >> >> the results are going to be wild if the models do not match.
>>
>> >> >> VLV
>>
>> >> > The drift is difficult to model. In the case of a Galvanic Skin
>> >> > Response (GSR), sometimes the baseline can be holding flat for many
>> >> > seconds, then all of a sudden it plunges downward.
>>
>> >> That isn't baseline, it's an as-yet unaccounted-for phenomenon that
>> >> you're measuring. There's information in that thar noise. Can you find a
>> >> way to use it?
>>
>> >> Jerry
>> >> --
>> >> Engineering is the art of making what you want from things you can get.
>> >> �����������������������������������������������������������������������
>>
>> > Baseline is the standard term for it. Baseline wander is caused by
>> > perspiration, body movement, etc. The actual response that is being
>> > measured is summed with the wandering baseline. Google "baseline
>> > wander" for more information.
>>
>> Isn't this just a fancy term for DC offset, or "slowly time-varying DC offset"?
>> If so, then couldn't it be removed with a DC notch filter? The IIR form doesn't
>> have too much of a delay.
>> --
>> % Randy Yates % "Ticket to the moon, flight leaves here today
>> %% Fuquay-Varina, NC % from Satellite 2"
>> %%% 919-577-9882 % 'Ticket To The Moon'
>> %%%% <ya...@ieee.org> % *Time*, Electric Light Orchestrahttp://www.digitalsignallabs.com
>
> The wandering baseline can sometimes move quickly, as in a rapid
> plunge, and a simple filter will probably attenuate the features that
> the analyst is trying to measure. That's why one turns to fairly
> exotic techniques for this problem, but holding down the delay in a
> real time instrument is difficult, as the OP obviously knows.
Hi John,
If the bandwidth of the interference intersects with the bandwidth
of the signal, then no linear filter technique (including wavelets)
will suffice. It seems in that case that the best possible solution
is to model the interference and design a canceller, as Vladimir
pointed out.
--
% Randy Yates % "Ticket to the moon, flight leaves here today
%% Fuquay-Varina, NC % from Satellite 2"
%%% 919-577-9882 % 'Ticket To The Moon'
%%%% <yates@ieee.org> % *Time*, Electric Light Orchestra
http://www.digitalsignallabs.com
Reply by John●December 27, 20072007-12-27
On Dec 27, 3:16 pm, "Poj" <netsir...@hotmail.com> wrote:
> Hi John,
>
> Thanks for message.
>
> Yes, you are right. Lag between input and output is too much. Do you have
> any articles, links or other information related to sliding DWT?
>
I only have what can be found with a search on IEEE Xplore or Google
Scholar.
John
Reply by John●December 27, 20072007-12-27
On Dec 27, 7:17 pm, Randy Yates <ya...@ieee.org> wrote:
> John <sampson...@gmail.com> writes:
> > On Dec 27, 5:56 pm, Jerry Avins <j...@ieee.org> wrote:
> >> John wrote:
> >> > On Dec 27, 12:59 pm, Vladimir Vassilevsky <antispam_bo...@hotmail.com>
> >> > wrote:
> >> >>>> If you are using a linear filter to resolve the frequencies, then the
> >> >>>> incurred delay can't be less then about 1/transition band.
> >> >>> Baseline wander removal is difficult in a realtime system for all the
> >> >>> reasons you cite.
> >> >> The only way to trick the nature is using parametric models of the
> >> >> signal and the drift. The parameters should be estimated as ML. However
> >> >> the results are going to be wild if the models do not match.
>
> >> >> VLV
>
> >> > The drift is difficult to model. In the case of a Galvanic Skin
> >> > Response (GSR), sometimes the baseline can be holding flat for many
> >> > seconds, then all of a sudden it plunges downward.
>
> >> That isn't baseline, it's an as-yet unaccounted-for phenomenon that
> >> you're measuring. There's information in that thar noise. Can you find a
> >> way to use it?
>
> >> Jerry
> >> --
> >> Engineering is the art of making what you want from things you can get.
> >> �����������������������������������������������������������������������
>
> > Baseline is the standard term for it. Baseline wander is caused by
> > perspiration, body movement, etc. The actual response that is being
> > measured is summed with the wandering baseline. Google "baseline
> > wander" for more information.
>
> Isn't this just a fancy term for DC offset, or "slowly time-varying DC offset"?
> If so, then couldn't it be removed with a DC notch filter? The IIR form doesn't
> have too much of a delay.
> --
> % Randy Yates % "Ticket to the moon, flight leaves here today
> %% Fuquay-Varina, NC % from Satellite 2"
> %%% 919-577-9882 % 'Ticket To The Moon'
> %%%% <ya...@ieee.org> % *Time*, Electric Light Orchestrahttp://www.digitalsignallabs.com
The wandering baseline can sometimes move quickly, as in a rapid
plunge, and a simple filter will probably attenuate the features that
the analyst is trying to measure. That's why one turns to fairly
exotic techniques for this problem, but holding down the delay in a
real time instrument is difficult, as the OP obviously knows.
John
Reply by Randy Yates●December 27, 20072007-12-27
John <sampson164@gmail.com> writes:
> On Dec 27, 5:56 pm, Jerry Avins <j...@ieee.org> wrote:
>> John wrote:
>> > On Dec 27, 12:59 pm, Vladimir Vassilevsky <antispam_bo...@hotmail.com>
>> > wrote:
>> >>>> If you are using a linear filter to resolve the frequencies, then the
>> >>>> incurred delay can't be less then about 1/transition band.
>> >>> Baseline wander removal is difficult in a realtime system for all the
>> >>> reasons you cite.
>> >> The only way to trick the nature is using parametric models of the
>> >> signal and the drift. The parameters should be estimated as ML. However
>> >> the results are going to be wild if the models do not match.
>>
>> >> VLV
>>
>> > The drift is difficult to model. In the case of a Galvanic Skin
>> > Response (GSR), sometimes the baseline can be holding flat for many
>> > seconds, then all of a sudden it plunges downward.
>>
>> That isn't baseline, it's an as-yet unaccounted-for phenomenon that
>> you're measuring. There's information in that thar noise. Can you find a
>> way to use it?
>>
>> Jerry
>> --
>> Engineering is the art of making what you want from things you can get.
>> �����������������������������������������������������������������������
>
> Baseline is the standard term for it. Baseline wander is caused by
> perspiration, body movement, etc. The actual response that is being
> measured is summed with the wandering baseline. Google "baseline
> wander" for more information.
Isn't this just a fancy term for DC offset, or "slowly time-varying DC offset"?
If so, then couldn't it be removed with a DC notch filter? The IIR form doesn't
have too much of a delay.
--
% Randy Yates % "Ticket to the moon, flight leaves here today
%% Fuquay-Varina, NC % from Satellite 2"
%%% 919-577-9882 % 'Ticket To The Moon'
%%%% <yates@ieee.org> % *Time*, Electric Light Orchestra
http://www.digitalsignallabs.com
Reply by John●December 27, 20072007-12-27
On Dec 27, 5:56 pm, Jerry Avins <j...@ieee.org> wrote:
> John wrote:
> > On Dec 27, 12:59 pm, Vladimir Vassilevsky <antispam_bo...@hotmail.com>
> > wrote:
> >>>> If you are using a linear filter to resolve the frequencies, then the
> >>>> incurred delay can't be less then about 1/transition band.
> >>> Baseline wander removal is difficult in a realtime system for all the
> >>> reasons you cite.
> >> The only way to trick the nature is using parametric models of the
> >> signal and the drift. The parameters should be estimated as ML. However
> >> the results are going to be wild if the models do not match.
>
> >> VLV
>
> > The drift is difficult to model. In the case of a Galvanic Skin
> > Response (GSR), sometimes the baseline can be holding flat for many
> > seconds, then all of a sudden it plunges downward.
>
> That isn't baseline, it's an as-yet unaccounted-for phenomenon that
> you're measuring. There's information in that thar noise. Can you find a
> way to use it?
>
> Jerry
> --
> Engineering is the art of making what you want from things you can get.
> �����������������������������������������������������������������������
Baseline is the standard term for it. Baseline wander is caused by
perspiration, body movement, etc. The actual response that is being
measured is summed with the wandering baseline. Google "baseline
wander" for more information.
John
Reply by Jerry Avins●December 27, 20072007-12-27
John wrote:
> On Dec 27, 12:59 pm, Vladimir Vassilevsky <antispam_bo...@hotmail.com>
> wrote:
>>>> If you are using a linear filter to resolve the frequencies, then the
>>>> incurred delay can't be less then about 1/transition band.
>>> Baseline wander removal is difficult in a realtime system for all the
>>> reasons you cite.
>> The only way to trick the nature is using parametric models of the
>> signal and the drift. The parameters should be estimated as ML. However
>> the results are going to be wild if the models do not match.
>>
>> VLV
>
> The drift is difficult to model. In the case of a Galvanic Skin
> Response (GSR), sometimes the baseline can be holding flat for many
> seconds, then all of a sudden it plunges downward.
That isn't baseline, it's an as-yet unaccounted-for phenomenon that
you're measuring. There's information in that thar noise. Can you find a
way to use it?
Jerry
--
Engineering is the art of making what you want from things you can get.
�����������������������������������������������������������������������
Reply by Jerry Avins●December 27, 20072007-12-27
Vladimir Vassilevsky wrote:
>
>
>>> If you are using a linear filter to resolve the frequencies, then the
>>> incurred delay can't be less then about 1/transition band.
>
>> Baseline wander removal is difficult in a realtime system for all the
>> reasons you cite.
>
> The only way to trick the nature is using parametric models of the
> signal and the drift. The parameters should be estimated as ML. However
> the results are going to be wild if the models do not match.
How about fixing the baseline? A muffler on the noise source is usually
more effective than noise-canceling earmuffs.
Jerry
--
Engineering is the art of making what you want from things you can get.
�����������������������������������������������������������������������
Reply by Poj●December 27, 20072007-12-27
Hi John,
Thanks for message.
Yes, you are right. Lag between input and output is too much. Do you have
any articles, links or other information related to sliding DWT?
Actually I have sliding wavelet kernels in my program for both DWT and
IDWT. However, since my wavelet can give the best result at Level 7, I
have to freeze the real-time data in the buffer to decompose the data to
Level 7, then extract the signal I want and reconstruct it back to Level
1. I am still looking for a better way to implement this in real-time
environment.
I combined Wavelet Denoising with bidirectional HPF (Wavelet Denoising
first, then forward HPF and finally backward HPF) to extract signal and
remove the baseline wander, gaussian white noise, and compensate phase
shift. This combination gives the best result over other stuff I have been
testing so far. The bidirectional HPF uses pure sliding kernels and does
not cause significant lag problem at all.
-poj
>
>Baseline wander removal is difficult in a realtime system for all the
>reasons you cite. I'm guessing you are driving some kind of display
>with the result, and can't tolerate much lag between stimulus and
>response. My hats off to you if you have found a satisfactory
>approach. There is a sliding DWT that you might look at.
>
>
>John
>