Specific-information

Short description: State-dependent measures that converge to the mutual information

In information theory, specific-information is the generic name given to the 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]\displaystyle{ I_V }[/math], [math]\displaystyle{ I_S }[/math], and [math]\displaystyle{ I_{ssi} }[/math]. The specific-information between a random variable [math]\displaystyle{ X }[/math] and a state [math]\displaystyle{ Y=y }[/math] is written as :[math]\displaystyle{ I( X ; Y = y) }[/math].

References

• Deweese, Michael; Meister, Markus (1999). "How to measure the information gained from one symbol". Network: Computation in Neural Systems 10 (4): 325–40. doi:10.1088/0954-898X/10/4/303. PMID 10695762. 
• Butts, Daniel (2003). "How much information is associated with a particular stimulus?". Network: Computation in Neural Systems 14 (2): 177–87. doi:10.1088/0954-898X/14/2/301. PMID 12790180.