Discrete stochastic processes and applications

Discrete Stochastic Processes and Applic

📁 Discrete Stochastic Processes and Applications

✍ Jean-François Collet 📂 Library 📅 2018 🏛 Springer 🌐 English

<p>This unique text for beginning graduate students gives a self-contained introduction to the mathematical properties of stochastics and presents their applications to Markov processes, coding theory, population dynamics, and search engine design. The book is ideal for a newly designed course in an

Discrete Stochastic Processes

📁 Discrete Stochastic Processes

✍ Robert G. Gallager (auth.) 📂 Library 📅 1996 🏛 Springer US 🌐 English

<p>Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time steps (for some time scale), or are characterized by discrete occurrences at arbitrary times. <em>Discrete Stochastic Processes</em> helps the reader develop th

Discrete stochastic processes

📁 Discrete stochastic processes

✍ Robert G. Gallager 📂 Library 📅 1995 🏛 Springer 🌐 English

Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time steps (for some time scale), or are characterized by discrete occurrences at arbitrary times. Discrete Stochastic Processes helps the reader develop the understand

Stoshastic processes and stochastic inte

📁 Stoshastic processes and stochastic integration

✍ Pivato M. 📂 Library 📅 1999 🌐 English

Discrete Stochastic Processes and Optima

📁 Discrete Stochastic Processes and Optimal Filtering

✍ Jean-Claude Bertein, Roger Ceschi 📂 Library 📅 2007 🏛 ISTE USA 🌐 English

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter pro

Discrete Stochastic Processes and Optima

📁 Discrete Stochastic Processes and Optimal Filtering

✍ Jean-Claude Bertein, Roger Ceschi 📂 Library 📅 2007 🏛 Wiley-ISTE 🌐 English

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter pro

Discrete stochastic processes and applications

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