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The convolutional coding with code and generator matrices are considered.
An example of a minimum bitrade is represented using generator matrices in the reduced echelon form.
Therefore, in order to exploit this correlation, the generator matrices are set exactly the same for all sensors.
The feature considered is the type of channel code, or more precisely the parameters and generator matrices of convolutional encoders.
This means that the encoder can construct generator matrices G N for any exponent n (N=2 n ).
By varying the free positions (marked with an "*") in this matrix, several polynomial generator matrices G(D) are produced.
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Table 1 summarizes the general rules for constructing the infinitesimal generator matrix of mode for a network with a general number of MoSN.
A transformation of the transition probabilities into transition rates is necessary to generate CTMC model with the same steady-state probabilities, but infinitesimal generator matrix of CTMC model is sparse.
where Q is the generator matrix.
where G N is called generator matrix.
where Q is the infinitesimal generator matrix.
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