https://en.formulasearchengine.com/w/api.php?action=feedcontributions&feedformat=atom&user=149.170.169.1formulasearchengine - User contributions [en]2026-08-06T10:04:57ZUser contributionsMediaWiki 1.47.0-wmf.7https://en.formulasearchengine.com/w/index.php?title=Bernoulli_space&diff=26720Bernoulli space2013-11-18T12:06:18Z<p>149.170.169.1: /* Future and past */</p>
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<div>{{Multiple issues|orphan = June 2011|no footnotes = May 2011|<br />
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In [[information theory]], '''specific-information''' is the generic name given to family of state-dependent measures that in expectation converge to the [[mutual information]]. There are currently three known varieties of specific information usually denoted <math>I_V</math>, <math>I_S</math>, and <math>I_{ssi}</math>.<br />
The specific-information between a random variable <math>X</math> and a state <math>Y=y</math> is written as,<br />
:<math>I( X ; Y = y)</math>.<br />
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==References==<br />
*{{cite journal |pages=325–40 |doi=10.1088/0954-898X/10/4/303 |title=How to measure the information gained from one symbol |year=1999 |last1=Deweese |first1=Michael |last2=Meister |first2=Markus |journal=Network: Computation in Neural Systems |volume=10 |issue=4 |pmid=10695762}}<br />
*{{cite journal |pages=177–87 |doi=10.1088/0954-898X/14/2/301 |title=How much information is associated with a particular stimulus? |year=2003 |last1=Butts |first1=Daniel |journal=Network: Computation in Neural Systems |volume=14 |issue=2 |pmid=12790180}}<br />
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[[Category:Information theory]]</div>149.170.169.1