Viterbi algorithm

For the identification of the optimal sequence of hidden metastable states we can use the well-known Viterbi algorithm [30], which exploits dynamic programming techniques to resolve in a recursive manner the optimization problem... 

All we require for actual synthesis are the coefficients C =< ci,C2,---Ct >, so the problem is to generate the highest probability sequence of these that also obeys the constraints of the delta coefficients AC =< Aci,Ac2,. .Acf >. As we have to find both the observations and the state sequence, we can t use the Viterbi algorithm as above but rather use an algorithm specific to this... 

See Jurafsky and Matrin [243] for an explanation of the DTW algorithm, its history and its relation to the Viterbi algorithm. 

As described in Section 15.1.5 the Viterbi algorithm seeks the highest probability path through an HMM network. The only real difference between that and unit selection search is that here we are trying to find the lowest cost path. This is in fact a trivial difference, and so the Viterbi algorithm as previously described can be used directly to find the lowest cost sequence of units in unit selection. 

As described in Section 15.1.5 the Viterbi algorithm seeks the highest-probabUity path through an HMM network. The only real difference between that and a unit-selection... 

In the paper the mathematical model of the methodology is presented. Model is based on Markov chains. The modified forward and modified Viterbi algorithms are used for simulations of processes. Binomial distribution is used to evaluate initial and transition probabilities. 

The modified forward and Viterbi algorithms are used to simulate the path in network system (disturbance consequence scenario). 

Andrew J. Viterbi [8]. After the introduction of Viterbi algorithm, many scientists and researchers extended this work by varying and improving the decoder design parameters in order to enhance the performance in software and hardware implementations. 

In Viterbi algorithm, after a transition from a state, the weights are calculated for each possible path. Whenever there is a difference in a particular received bit and the state output bit, one is added to the previous accumulated weight in the... 

The Viterbi algorithm is based on trellis expansion operation. During the execution of Viterbi algorithm implemented in assembly language programming, code for trellis expansion function is executed multiple times. For example, if there are 12 bits in a received codeword then this trellis function is called approximately nineteen times, as shown in Fig. 4.2. 

Table 4.8 shows the comparison of the performance of Viterbi algorithm, in particular, trellis expansion function, when implemented in DUX assembly language and with custom Texpand instruction. This instruction is called nineteen times in the Viterbi algorithm for 6-bit decoding. The results show substantial improvement of three times when trellis expands function is implemented as a custom instruction. 

---