That is straightforward.
In High SNR, the lazy algorithm is O(1)!!!
In low SNR, both the lazy algorithm and the traditional algorithm are
both O(2^k) where k+1 is the constraint length.
It is not a simple relationship as the SNR falls off but in many of the
cases we would consider, the lazy algorithm should be a win.
Bob
Matt Ettus wrote:
Michael Dickens wrote:
I'm working on programming the "Lazy" Viterbi (convolutional, maximum
likelihood) decoder right now. See
< http://citeseer.ist.psu.edu/599573.html >
< http://vanu.com/resources/publications/
2002fast_maximum_likelihood_decoder.pdf >
Mike,
Can't help you with the algorithm, but could you say a few words on the
advantages of Lazy Viterbi over normal Viterbi decoding?
Matt
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