I will rephase your question as "What is a finite Markov chain processes?" If this is not your question, please resubmit it. As I researched this question, I found an interesting information on the Markov's, as his brother and brother's son contributed to mathematics. See: http://en.wikipedia.org/wiki/Andrey_Markov How much of Markov chain theory actually orginated with Andrey or future generations of Markov's and others is a good question. Commonly, mathematicians name their theories to other famous mathematicians, for example, Bayes, Gauss & Bernoulli. A Markov chain is a hypothetical process that has finite and identifiable states. The system changes in discrete steps, and only the current state will have an affect of the future state. I will use a concrete example of this. I'm hungry and standing in line at McDonalds. Suppose there are a finite number of choices, say 1- 12 (yes I know this is not true, but just suppose it, ok). Now suppose that my choice is not completely random, but is affected by what the person ahead of me is choosing. If the person ahead of me chooses a number 1, I will have have a higher chance of choosing a number 1 (say for example 50%) and a lower chance of choosing all other options. I could run a simulation model where thousands of customers are served and find out what are the probabilities of number 1 to 13 being served. The state of the system is determined by the selections of the customer defined by an unchanging set of rules governing the probability. In a more general sense, we could have a fix set of rules (conditional probabilities), that state given what the last customer ordered, will determine the probabilities of the next customer. This is called a transition matrix of probabilities. You can find more examples at: http://en.wikipedia.org/wiki/Examples_of_Markov_chains which cites the board game of monopoly as an example of Markov chain, because given the square that you are currently on, will determine the probabilities of the "future state" or the next square on which you will land.
A continuous-time stochastic process is called a semi-Markov process or 'Markov renewal process' if the embedded jump chain (the discrete process registering what values the process takes) is a Markov chain, and where the holding times (time between jumps) are random variables with any distribution, whose distribution function may depend on the two states between which the move is made. A semi-Markov process where all the holding times are exponentially distributed is called a continuous time Markov chain/process
Internal labour supply.
Please consult some book.
theory of zonar diod
Slide Theory Stupid!!
Andrey Markov is notable mathematician known for proving mathematical theories like Markov Brothers' Inequality, Markov chains and Markov processes. Some of his other contributions are solving linear differential equations, constructive mathematics and recursive functions theory.
E. B Dynkin has written: 'Theory of Markov processes' -- subject(s): Markov processes
A. A. Markov has written: 'Differenzenrechnung' -- subject(s): Difference equations, Interpolation 'The Correspondence between A.A. Markov and A.A. Chuprov on the theory of Probability and Mathematical statistics' -- subject(s): Correspondence, Mathematical statistics, Mathematicians, Probabilities '[Izbrannye trudy' -- subject(s): Bibliography, Number theory, Probabilities
Martin L. Silverstein has written: 'Symmetric Markov processes' -- subject(s): Markov processes, Potential theory (Mathematics)
Brian Marcus has written: 'Entropy of hidden Markov processes and connections to dynamical systems' -- subject(s): Dynamics, Entropy (Information theory), Congresses, Markov processes
The author Mark Efimovich Markov is known for his work in mathematics and probability theory, particularly for his development of the mathematical concept of Markov chains. His contributions to the field have had a significant impact on various areas such as statistics, physics, biology, and computer science.
He has worked for many years in probability theory and I suggest that he is best known for his work with Markov chains.
A. Federgruen has written: 'Markovian control problems' -- subject(s): Control theory, Markov processes
Aleksandr Markov's birth name is Aleksandr Vladimirovitch Markov.
Andrei Markov's birth name is Andrei Viktorovich Markov.
Evgeniy Markov's birth name is Yevgeniy Lvovitch Markov.
Leonid Markov's birth name is Markov, Leonid Vasilyevich.