On 06/26/2015 11:08 PM, Les Cargill wrote:
> Phil Hobbs wrote:
> <snip>
>>
>> (I once tried something reminiscent of that to improve loop stability of
>> a PLL.  It turned out that I'd made an algebra error, and was in fact
>> trying to make a time machine.  It didn't work.) ;)
>>
>
> I've been trying to make a time machine* all week. It's damned
> difficult, I must say!
>
> *In this case, a filter with alpha of 0.001 with no delay. Er
> rather, a filter plus some other furniture. Or, as
> it turns out, not. Stupid Second Law!

Gummint has time machines. But they don't much understand how they work. 
They ship things off into time but they don't come back until much 
later. They have no idea where they went.



-- 

       ___           ___           ___            ___
      /\  \         /\  \         /\__\          /\  \
     /::\  \       /::\  \       /::|  |         \:\  \
    /:/\:\  \     /:/\:\  \     /:|:|  |     ___ /::\__\
   /::\~\:\__\   /::\~\:\  \   /:/|:|  |__  /\  /:/\/__/
  /:/\:\ \:|__| /:/\:\ \:\__\ /:/ |:| /\__\ \:\/:/  /
  \:\~\:\/:/  / \:\~\:\ \/__/ \/__|:|/:/  /  \::/  /
   \:\ \::/  /   \:\ \:\__\       |:/:/  /    \/__/
    \:\/:/  /     \:\ \/__/       |::/  /
     \::/__/       \:\__\         /:/  /
      ~~            \/__/         \/__/

Phil Hobbs wrote:
<snip>
>
> (I once tried something reminiscent of that to improve loop stability of
> a PLL.  It turned out that I'd made an algebra error, and was in fact
> trying to make a time machine.  It didn't work.) ;)
>

I've been trying to make a time machine* all week. It's damned 
difficult, I must say!

*In this case, a filter with alpha of 0.001 with no delay. Er
rather, a filter plus some other furniture. Or, as
it turns out, not. Stupid Second Law!

> Cheers
>
> Phil Hobbs
>
>
>
>

-- 
Les Cargill

On 4/19/2012 2:43 PM, Bret Cahill wrote:
> I just assumed "matched filtering" included the deconvolution and
> other steps to recover the original signal's shape.
>
> In this case it was actually easier to invent a new filter -- I
> assumed it already existed --  than to be scholarly and do some
> research.
>
> To avoid confusion with the terminology from now on the filter that
> takes the convolution of a noisy signal like a conventional matched
> filter and then takes the deconvolution to recover the original wave
> form should be called "signal recovery matched filtering."
>
> This will distinguish it from the signal detection matched filter
> _even if the new filter is used for signal detection_.
>
> I've updated http://www.bretcahill.com to reflect the new terminology.
>
> If anyone can think of a better name, i.e., the "Cahill Filter" please
> post.
>

Filtering (convolution) in the time domain is multiplication in the 
frequency domain, and is therefore associative.  If you apply a filter F 
and its inverse F^-1 to a signal G,


F^-1 (F G) = (F^-1 F) G = G.

No free lunch, I'm afraid.

(I once tried something reminiscent of that to improve loop stability of 
a PLL.  It turned out that I'd made an algebra error, and was in fact 
trying to make a time machine.  It didn't work.) ;)

Cheers

Phil Hobbs




-- 
Dr Philip C D Hobbs
Principal Consultant
ElectroOptical Innovations LLC
Optics, Electro-optics, Photonics, Analog Electronics

160 North State Road #203
Briarcliff Manor NY 10510

hobbs at electrooptical dot net
http://electrooptical.net

> I just assumed "matched filtering" included the deconvolution and
> other steps to recover the original signal's shape.
>
> In this case it was actually easier to invent a new filter -- I
> assumed it already existed -- &#4294967295;than to be scholarly and do some
> research.
>
> To avoid confusion with the terminology from now on the filter that
> takes the convolution of a noisy signal like a conventional matched
> filter and then takes the deconvolution to recover the original wave
> form should be called "signal recovery matched filtering."
>
> This will distinguish it from the signal detection matched filter
> _even if the new filter is used for signal detection_.
>
> I've updatedhttp://www.bretcahill.comto reflect the new terminology.
>
> If anyone can think of a better name, i.e., the "Cahill Filter" please
> post.



Deconvolution Match Filtering

Specific Match Filtering

Integration Free Match Filtering

No Low Pass Match Filtering

Dedicated Matched Filtering


Bret Cahill

On Apr 19, 2:43=A0pm, Bret Cahill <BretCah...@peoplepc.com> wrote:
> I just assumed "matched filtering" included the deconvolution and
> other steps to recover the original signal's shape.
>
> In this case it was actually easier to invent a new filter -- I
> assumed it already existed -- =A0than to be scholarly and do some
> research.
>
> To avoid confusion with the terminology from now on the filter that
> takes the convolution of a noisy signal like a conventional matched
> filter and then takes the deconvolution to recover the original wave
> form should be called "signal recovery matched filtering."
>
> This will distinguish it from the signal detection matched filter
> _even if the new filter is used for signal detection_.
>
> I've updatedhttp://www.bretcahill.comto reflect the new terminology.
>
> If anyone can think of a better name, i.e., the "Cahill Filter" please
> post.
>
> Bret Cahill

A Confederacy of Dunces filter.

On Sun, 22 Apr 2012 15:00:16 -0400, Randy Yates wrote:

> if (bretCahillPostedInCompDSP)
> {
>   compDSP.SNR -= 10; /* derate SNR by 10 dB */
> }

Please don't feed the troll.

-- 
My liberal friends think I'm a conservative kook.
My conservative friends think I'm a liberal kook.
Why am I not happy that they have found common ground?

Tim Wescott, Communications, Control, Circuits & Software
http://www.wescottdesign.com

One minor off point omission:

Simply clicking in noise as on the Joy of Convolution applet example
doesn't just add noise;  It subtracts some of the signal as well.

But even then match filtering works.


Bret Cahill


> > =A0 compDSP.SNR -=3D 10
>
> OK, everyone already knows you are floundering.
>
> Here, try again:
>
> Conventional matched filtering should really be understood as a
> truncated version of the signal recovery method in the Excel example
> athttp://www.bretcahill.com.
>
> It sounds counter intuitive but by omitting the signal recovery steps
> traditional match filtering has the often desirable additional effect
> of low pass filtering. Since noise is often at a higher frequency than
> signals few were willing to question a situation where you get 2
> filters just by being too lazy to complete what should be considered
> the first filtering operation.
>
> Even when signal detection is all that is desired, however, it would
> be better to separate what should really be treated two distinct
> processes. Recover the original signal by taking the deconvolution of
> the match filter output, and then, if any additional frequency
> filtering in necessary, tailor it to the situation and to your needs.
>
> And, of course, when it comes to signal recovery this should be the
> optimal filter.
>
> Bret Cahill

On 22/04/2012 20:00, Randy Yates wrote:
> if (bretCahillPostedInCompDSP)
> {
>    compDSP.SNR -= 10; /* derate SNR by 10 dB */
> }

Put the clueless troll in your killfile and be done with it!

-- 
Regards,
Martin Brown

> =A0 compDSP.SNR -=3D 10

OK, everyone already knows you are floundering.

Here, try again:

Conventional matched filtering should really be understood as a
truncated version of the signal recovery method in the Excel example
at http://www.bretcahill.com.

It sounds counter intuitive but by omitting the signal recovery steps
traditional match filtering has the often desirable additional effect
of low pass filtering. Since noise is often at a higher frequency than
signals few were willing to question a situation where you get 2
filters just by being too lazy to complete what should be considered
the first filtering operation.


Even when signal detection is all that is desired, however, it would
be better to separate what should really be treated two distinct
processes. Recover the original signal by taking the deconvolution of
the match filter output, and then, if any additional frequency
filtering in necessary, tailor it to the situation and to your needs.

And, of course, when it comes to signal recovery this should be the
optimal filter.


Bret Cahill