- 'effects' (Canon
ExpSim LV). The
first general-use interchangeable-lens
DSLRs with live view for both
exposure simulated live
preview (
ExpSim LV) and framing...
-
microphone Live
preview with
ExpSim LV "exposure simulation" live
preview (full
exposure preview control utilizing ExpSim LV, a
first for
video in a DSLR)...
- that E 0 ∼
Exp ( 6 ) {\displaystyle E_{0}\
sim {\text{
Exp}}(6)} , E 1 ∼
Exp ( 12 ) {\displaystyle E_{1}\
sim {\text{
Exp}}(12)} and E 2 ∼
Exp ( 18 ) {\displaystyle...
- that if X ∼ χ 2 2 {\displaystyle X\
sim \chi _{2}^{2}} , then X ∼
exp ( 1 2 ) {\displaystyle X\
sim \operatorname {
exp} \left({\frac {1}{2}}\right)} is...
- with
shape parameter 1. If X ~
Exp(λ) and Xi ~
Exp(λi) then: k X ∼
Exp ( λ k ) {\displaystyle kX\
sim \operatorname {
Exp} \left({\frac {\lambda }{k}}\right)}...
-
function is f ( x ∣ μ , b ) = 1 2 b
exp ( − | x − μ | b ) , {\displaystyle f(x\mid \mu ,b)={\frac {1}{2b}}\
exp \left(-{\frac {|x-\mu |}{b}}\right),}...
- {\displaystyle Y\
sim \operatorname {IG} (a\mu ,a\lambda )} . The
standard form of
inverse Gaussian distribution is f ( x ; 1 , 1 ) = 1 2 π x 3
exp ( − ( x...
- Inequality—Let Z ∼ N ( 0 , 1 ) {\displaystyle Z\
sim N(0,1)} . Then P ( | Z | > t ) ≤ 2 π
exp ( − t 2 / 2 ) t ≤
exp ( − t 2 / 2 ) t {\displaystyle \operatorname...
- {\boldsymbol {X}}\
sim {\mathcal {N}}({\boldsymbol {\mu }},\,{\boldsymbol {\Sigma }})} is a
multivariate normal distribution, then Y i =
exp ( X i ) {\displaystyle...
- F − 1 {
exp [ − j ω μ X ]
exp [ − σ X 2 ω 2 2 ]
exp [ − j ω μ Y ]
exp [ − σ Y 2 ω 2 2 ] } = F − 1 {
exp [ − j ω ( μ X + μ Y ) ]
exp [ − (...
