Re: What databases have taught me

From: topmind <>
Date: 23 Jun 2006 22:06:01 -0700
Message-ID: <>

Neo wrote:

> > However, I am not saying that relational is best for every structuring need; just the majority of what I encounter in my domain.
> I agree that a more general method will typically be less efficient
> than a less general method that is optimized for a certian
> domain/scope. While RM is well suited for many common apps, it is not
> as suitable for say AI-type apps where data structures are not only
> highly variable but unknown in advance which makes a methodolgy where a
> schema has to be updated, less practical.


Our very *brain* can be modelled more or less with a "static schema", I would note:

  table: Links

  weight // weighting factor, can be negative in some models

  table: Node

  activationFuncIndicator // see note
  activationWeight // the "volume" given to activation function

There are about 5 activation functions in common use: unit_step, sigmoid, piecewise_linear, gaussian, and identity. (I haven't reviewed my schema model closely, so buyer beware. This model allows "Y splits", which real neurons don't directly allow IIRC, but can be modeled with explicit neurons such that they are still interchangable.)

-T- Received on Sat Jun 24 2006 - 07:06:01 CEST

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