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From matrix inversion lemma [33], the inverse matrix of J is: (21).
It can be verified via applying the matrix inversion lemma that the inverse of B i is equal to B i - 1 = B i, - j - 1 - γ j B i, - j - 1 Φ i, j Φ i, j T B i, - j - 1 1 + γ j Φ i, j T B i, - j - 1 Φ i, j.
The inverse matrix of φ can be derived further by matrix inversion lemma (MIL) [38]: φ - 1 = σ n - 2 I - σ n - 4 C σ n - 2 C H C + I - 1 C H = σ n - 2 I - σ n - 4 σ n - 2 + 1 CC H. where the second equality uses the result of CH C = I.
A variation of the matrix inversion lemma provides us with a useful closed-form expression of the inverse covariance matrix model, i.e., (54).
Meanwhile, LTR principles are analyzed and proved theoretically by adopting the matrix inversion lemma.
First, we review the recursive 4SID algorithm based on the matrix inversion lemma shown in our previous paper.
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Before we investigate the convergence property of SO-DCTS algorithm with Gaussian delay, we give the following lemma for block matrix inversion.
Thus, computing the inversion of matrix W RZF can be transformed into computing the inversion of matrix L. Continue to utilize the Sherman-Morrison lemma [12] to iterate the process of computing the L ′ s matrix inversion.
This lemma inspires us that we can utilize iteratively method to calculate several times' simple matrix inversion instead of computing directly complex matrix inversion and eventually simplify the high computational complexity to lower computational complexity.
To solve this problem, we utilize the Cholesky-decomposition and Sherman-Morrison lemma and propose CSM (Cholesky and Sherman-Morrison strategy -based precoding strategy -basedatrix inversion by exprecodingthe aschemetocally orthegonal channel property in matrixe Minversionms.
The inverse matrix in Equation 32 can be computed according to Strassen's matrix inversion algorithm.
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