Viterbi Algorithm

@inproceedings{Forney2010ViterbiA,
  title={Viterbi Algorithm},
  author={Jr. G. Forney},
  booktitle={Encyclopedia of Machine Learning},
  year={2010}
}
  • Jr. G. Forney
  • Published in
    Encyclopedia of Machine…
    1 March 1973
  • Computer Science
The Viterbi algorithm (VA) is a recursive optimal solution to the problem of estimating the state sequence of a discrete-time finite-state Markov process observed in memoryless noise. Many problems in areas such as digital communications can be cast in this form. This paper gives a tutorial exposition of the algorithm and of how it is implemented and analyzed. Applications to date are reviewed. Increasing use of the algorithm in a widening variety of areas is foreseen. 

Extended Viterbi Algorithm for Hidden Markov Process: A Transient/Steady Probabilities Approach

TLDR
An extended Viterbi algorithm is presented for first-order hidden Markov processes, with the help of a dummy combined state sequence, and also picks up the state switching earlier, which is particularly important for the out of sample applications.

Large Deviation Bounds for Functionals of Viterbi Paths

TLDR
The aim of this paper is to provide the corresponding large deviation estimates of the maximum a posteriori estimator based on a finite number of observations of the hidden Markov model through available observations.

The Viterbi Algorithm

TLDR
A proposal for further research into the use of the Viterbi Algorithm in Signature Verification is presented, and is the area of present research at the moment.

The Viterbi Algorithm 1 1 The Viterbi Algorithm .

TLDR
A proposal for further research into the use of the Viterbi Algorithm in Signature Verification is presented, and is the area of present research at the moment.

Parameters Identiication of a Time-varying Stochastic Dynamic Systems Using Viterbi Algorithm

TLDR
A new algorithm based on the Viterbi algorithm developped for decoding convolutional codes is presented that applies the dynamic programming principle to the detection of discrete-time nite state Markov processes with noisy observation.

The Viterbi Algorithm for Subset Selection

TLDR
A new method based on the computationally efficient Viterbi algorithm is proposed which is shown to achieve better performance than competing algorithms such as Orthogonal Matching Pursuit (OMP), orthogonal Least-Squares (OLS), Multi-Branch Matching pursuit (MBMP), Iterative Hard Thresholding (IHT), and l1 minimization.

Constrained multiple model maximum a posteriori estimation using list Viterbi algorithm

TLDR
A new approach for constrained multiple model (MM) maximum a posteriori (MAP) estimation through the expectation-maximization (EM) method by using the previously developed constrained sequential list Viterbi algorithm (CSLVA).

ViterbiNet: Symbol Detection Using a Deep Learning Based Viterbi Algorithm

TLDR
ViterbiNet is a data-driven symbol detector obtained by converting the Viterbi algorithm into a system utilizing deep neural networks (DNNs), which operates without CSI and demonstrates the conceptual benefit of designing DNN-based communication systems to implement established algorithms.

Analysis of the Viterbi Algorithm Using Tropical Algebra and Geometry

  • E. TheodosisP. Maragos
  • Computer Science
    2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
  • 2018
TLDR
This work analyzes the Viterbi algorithm in the field of tropical (min-plus) algebra, and utilizes its pruning variant in order to define a polytope, and interprets certain faces of the polytopes as the most probable states of the algorithm.

Equivalence of ML decoding to a continuous optimization problem

TLDR
This work proves that the ML estimation of a discrete input sequence (with no assumptions on the encoder/channel used) is equivalent to the solution of a continuous non-convex optimization problem, and that this formulation is closely related to the computation of symbolwise MAP estimates.
...

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TLDR
The problems of reducing the Viterbi algorithm to hardware, the various tradeoffs and compromises that must be made, and the short cuts that are available are described.

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