Answer:
Fredholm's integral equations of the first kind are the prototypical example of ill-posed linear inverse problems. The model, among other things, reconstruction of distorted noisy observations and indirect density estimation and also appear in instrumental variable regression. However, their numerical solution remains a challenging problem. Many techniques currently available require a preliminary discretization of the domain of the solution and make strong assumptions about its regularity. For example, the popular expectation-maximization smoothing (EMS) scheme requires the assumption of piecewise constant solutions which is inappropriate for most applications. We propose here a novel particle method that circumvents these two issues. This algorithm can be thought of as a Monte Carlo approximation of the EMS scheme which not only performs an adaptive stochastic discretization of the domain but also results in smooth approximate solutions. We analyze the theoretical properties of the EMS iteration and of the corresponding particle algorithm. Compared to standard EMS, we show experimentally that our novel particle method provides state-of-the-art performance for realistic systems, including motion deblurring and reconstruction of cross-section images of the brain from positron emission tomography.
Step-by-step explanation:
Answer:
Similar-AA
Step-by-step explanation:
If you know 2 angles of the triangle you automatically know the third. If all the corresponding angles of two triangles are the same, they are similar.
(p.s. This sign ~ means similar)
Answer:
9.2
Step-by-step explanation:
So the 14 can be divided equally on both sides by the fact that the line cutting it at right angle bisects it.
Thus having 6 and 7 as the two shorter sides of a right angled triangle will help us get the radius( hypotenuse in this case) using the square root of the sum of the squares of both six and 7, the Pythagoras theory.
this leads to 9.2 as our answer
Answer:
it's a) the variable y represents the pounds of cookies sold in the $63 purchase
hope it helps;)
