[SI-LIST] Re: model to measurement correlation - (taken from Re: 2D vs 3D EM based signal integrity simulators)
- From: "Jason R. Miller" <Jason.R.Miller@xxxxxxx>
- To: "Grossman, Brett" <brett.grossman@xxxxxxxxx>
- Date: Mon, 25 Jan 2010 14:45:30 -0500
Hi Brett,
There is an implementation of this method that is available. I'd contact
Bruce to get the latest version of the code (barch@xxxxxxxxxx). Last
time I downloaded it, I got it from this site:
http://ing.univaq.it/uaqemc/
As of early 2009, the latest version of the code was 1 D FSV 4.0.3L.
Thanks
Jason
Grossman, Brett wrote:
> Thanks Jason.
>
> I recall Bruce Archambeault of IBM referencing FSV in a DesignCon
> presentation 4 or 5 years ago. As I understood it at the time, FSV seemed
> like a very useful method to replicate the way engineers visually analyze
> data (like what I describe as the eyeball method, but more
> repeatable/consistent). Are you aware if anyone has made an implementation
> of this method generally available? It would be cool to perform a comparison
> between what folks use...
>
> Thanks again,
> -Brett
>
>
>
> -----Original Message-----
> From: Jason.R.Miller@xxxxxxx [mailto:Jason.R.Miller@xxxxxxx]
> Sent: Monday, January 25, 2010 10:08 AM
> To: Grossman, Brett
> Cc: si-list@xxxxxxxxxxxxx
> Subject: Re: [SI-LIST] model to measurement correlation - (taken from Re: 2D
> vs 3D EM based signal integrity simulators)
>
> Feature Selective Validation (FSV) is a good technique for quantifying
> the data comparison between simulated and measured s-parameters:
>
> https://www.dora.dmu.ac.uk/xmlui/handle/2086/279
>
> Jason Miller
>
> Grossman, Brett wrote:
>
>> For my own curiosity...
>> I've seen the term 'correlation' used a lot when considering whether
>> s-parameter simulation results (a.k.a. model results) agree with
>> measurements. I am curious as to what people on this list generally
>> consider as correlation.
>>
>> To achieve a measure of 'correlation', what I've personally observed being
>> applied much of the time is a technique we call "The Eyeball Method." Use
>> of this technique is often characterized by the user making some statement
>> like "you can 'see*' that the measured and simulated insertion loss curves
>> are right on top of each other." I'd say in the majority of papers I review
>> this is the method employed.
>>
>> [*hence the reason we call it the eyeball method]
>>
>> Probably the next most common method I've seen is to take a scalar
>> difference between a measured and simulated response, and allow the residual
>> to be the measure of agreement. This is probably the second most used
>> method in papers I review, and it is a very distant second (IMHO).
>>
>> We presented a method based on EVM a couple years ago which maintains the
>> vector nature of the data to a degree. It was meant to compare a simulation
>> to a distribution of measurements, but has also been applied to one
>> measurement vs. one simulation comparisons.
>>
>> There are other methods we've described in past papers, and I believe that
>> all of these methods have their place. I don't think I could describe them
>> as well as I can if I hadn't used them all myself, so I don't feel as if I
>> am picking on anyone by asking a question.
>>
>> What I am curious about from this list is:
>>
>>
>> 1. What method do you use to quantitatively describe the agreement between
>> simulated and measured s-parameters?
>>
>> Any comments?
>>
>> Thanks,
>> -Brett
>> Brett Grossman
>> Sr. Staff SI Engineer
>> Signal Integrity Pathfinding - Sort Test Technology Development
>> [cid:image001.gif@01CA9DA3.2E08F710]<http://www.linkedin.com/in/brettgrossman>
>>
>>
>>
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>>
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