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Note that the decoding matrix is initialized as (25).
Second, the clusters are separated into three categories and the membership matrix is initialized.
In the first step, the matrix is initialized with k random solutions.
When the membership matrix is initialized, we select the virtual center in advance.
The state of the system at each time instant t is a K × K matrix S. The state matrix is initialized to the all-zeros matrix.
In the first iteration of BIRLS method, the weight matrix is initialized to the identity matrix which means a regular LS is applied.
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The activity and the transformation matrix were initialized with non-negative random values.
Initially, the community matrix was initialized to all zeroes; later, this matrix was populated with community numbers such that if a node i belonged to community k, then the element Community_Matrix [i, k] consists of k.
Meanwhile, for each new state variable y i, the corresponding covariance matrix are initialized according to P k ∣ k n e w = J P k ∣ k 0 0 0 R i 0 0 0 σ ρ 2 J T (16) J = I 0 ∂ y ∂ r W ∂ y ∂ ϕ C 0 ⋯ 0 ∂ y ∂ z i ∂ y ∂ ρ i (17).
The differences from the original algorithm are (i) all the borders of the matrix are initialized to infinity to ensure that the alignment starts at the endpoint and (ii) the scores can drop <0 to ensure the found startpoint is connected to the endpoint.
Both matrices are initialized with the value 0 in all cells: frac{partial C} {partial f_{u} (t)} = 0 ;, 1 leq t leq T, forall u in U !!!quad! text{and}!! quad! frac{partial C} {partial A_{u, v}} = 0 ; forall u, v in U. (12).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com