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Using the resistance spot welding process as an example, this paper presents a new robust design and analysis framework for products and processes with parameter interdependency.
As in the first scheme, arrival and service rates of PUs are characterized by a set of Poisson processes with parameter λ PU i and an exponential distribution with parameter μ PU i, respectively.
Then, for a period of T time-bins (the length of the activation period), the activated sources were driven by independent geometric processes with parameter pb = fb Δt.
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The PRN user distributions are modeled as homogeneous Poisson random processes with parameters ρ i representing the user density of the i th PRN.
E-optimal designs for comparing three treatments in blocks of size three are identified, where intrablock observations are correlated according to a first order autoregressive error process with parameter ρ∈ 0,1).
The traffic at every node is an independent identical (iid) Poisson process with parameter λ. 2.
After subgroup 100, observations are generated from an out-of-control process with parameter vector [N', P1'].
The packet arriving process for a node is an independent identical Poisson process with parameter λ, then the total traffic in the network with n nodes can be viewed as a Poisson process with parameter n λ.
It models the occurrence of FAR events as a Poisson process with parameter λ FAR with a theoretical justification based on a shrinking Bernoulli process [13].
The jumps are all independents with law and the times where the jumps occur follow the law of a standard Poisson process with parameter.
Assume that the users arrive as a Poisson process with parameter, and their active times in the system follow the exponential distribution with mean 10 seconds.
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