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be generalized reflection matrices.
Problem I Let P j ∈ R m j × m j and Q j ∈ R n j × n j be generalized reflection matrices.
Let P ∈ R m × m and Q ∈ R n × n be two real generalized reflection matrices, i.e., P T = P, P 2 = I m, Q T = Q, Q 2 = I n, I n denotes the n order identity matrix.
Algorithm 2.1 Step 1: Input matrices A i j ∈ R r i × m j, B i j ∈ R n j × s i, M i ∈ R r i × s i, and generalized reflection matrices P j ∈ R m j × m j and Q j ∈ R n j × n j, i = 1, …, p, j = 1, …, q ; Step 2: Choose an arbitrary matrix group ( X 1 ( 1 ), X 2 ( 1 ), …, X q ( 1 ) ) ∈ R r m 1 × n 1 ( P 1, Q 1 ) × R r m 2 × n 2 ( P 2, Q 2 ) × ⋯ × R r m q × n q ( P q, Q q ).
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Three different numerical approaches to overcome the local mass conservation problem of the random walk methodology are examined: (i) the interpolation method, (ii) the reflection principle, and (iii) the generalized stochastic differential equations (GSDE).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com