What they really mean by "compressed sensing" is imputation of sense data missing from the data actually sensed. In other words, they are trying to synthesize data that wasn't _actually_ sensed in the first place. The optimal theoretic solution is to losslessly compress the data actually sensed to the smallest computer program that outputs the data and then use the resulting program to impute the data that wasn't sensed -- just as with any prediction from a Solomonoff Induced model. Since this optimal theoretic solution is impractical, they there is a subdiscipline called 'signal processing' in which the technique _called_ "compressed sensing" may be applied but only subject to "... two conditions under which recovery is possible."
On Thu, Nov 4, 2021 at 2:41 PM John Rose <[email protected]> wrote: > PM, WriterOfMinds wrote: > > And the hybrid compressor as a whole is lossy. (Any lossy step in the > process makes the final output lossy.) > > > The hybrid compressor. There are many. > > I forget - was "Compressive Sensing" considered lossy? > https://en.wikipedia.org/wiki/Compressed_sensing > > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + > delivery options <https://agi.topicbox.com/groups/agi/subscription> > Permalink > <https://agi.topicbox.com/groups/agi/T5ff6237e11d945fb-M46126c2af4a0019f62bab591> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T5ff6237e11d945fb-M6910beaaf9525b0a1a467524 Delivery options: https://agi.topicbox.com/groups/agi/subscription
