Markov Models: Theory, Algorithms and Applications

This book is a discussion of Markov models. The author begins by explaining what Markov models are. This helps the reader in familiarizing themselves with the basics of Markov models including states, processes, transitions and others. The various algorithms in Markov models have been discussed. You will know how to work with these algorithms when modeling systems. Markov models are applied in a wide range of fields. The author helps the reader understand how Markov models can be applied in dynamic system modeling and diagnostics. This is because Markov models can be used to identify faults in systems. You will know how to use these models to identify any faults in your systems. Markov models are also used in exploration of three-dimensional protein structure. The author helps the reader understand how this is done. The use of Markov models in neurosciences has been explored; hence you will know the various fields in neuroscience where they are applied. ECG characterization is also another application area of Markov models. This book helps you understand this process in depth.
The following topics have been explored in this book:
- Understanding a Markov Model
- Algorithms
- Dynamic System Modelling and Diagnosis
- Exploration of Three-Dimensional Protein Structure
- Markov Models in Neurosciences
- ECG Characterization