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We treat the problem of modeling events happening randomly in time at a rate determined by some other random signal process.
This paper hopes to illustrate the role of martingale theory in the modeling of signals in discontinuous observations. Processes with jumps arise when “events” ...
We treat the problem of modeling events happening randomly in time at a rate determined by some other random "signal" process. It is shown that a martingale ...
We treat the problem of modeling events happening randomly in time at a rate determined by some other random “signal” process. It is shown that a martingale ...
The Modeling of Randomly Modulated Jump Processes. Adrian Segall, Thomas Kailath. Massachusetts Institute of Technology; Stanford University. Research output ...
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A jump process is a stochastic process that makes transitions between discrete states at times that can be fixed or random. In such a process, the system enters ...
Apr 4, 2020 · Jump models also allow the magnitude of the jumps to be random. ... Jump-diffusion models combine a jump process and a standard diffusion.
Genetic recombination is one of the most important mechanisms that can generate and maintain diversity, and recombination information plays an important ...
Given a random vector J in Rd defined on some probability space (Ω,P), the distribution of J is the mapping ρ defined on sets A ⊂ Rd as follows: ρ(A) := P(J ∈ A) ...
Missing: modulated | Show results with:modulated