by Pratik Lahiri

Hidden Markov Models

When ground water evaporates, dust in the clouds and low temperature gives a chance of snow. Weather and many other complex systems have many internal components (water, dust, temperature) that interact with each other to generate an observable effect (snow). The hidden Markov model is the simplest dynamic Bayesian network that models the internal of a complex system as a Markov chain.

Presentation Summary

In this presentation, I introduce algorithms to evaluate an established hidden Markov model and touch on how these models may be generated

References

All Quantum Computing