کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4634126 | 1340686 | 2008 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution](/preview/png/4634126.png)
چکیده انگلیسی
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of conservation law equations is proposed. This framework allows us to demonstrate an intrinsic link between microscopic and macroscopic models for evolution via the concept of perturbed generalized dynamic systems. The main result is exemplified with a number of illustrative examples where efficient numerical approximations follow directly from network-based computational models, viewed here as Markov chain approximations. Finally, stability and consistency conditions of such computational models are discussed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematics and Computation - Volume 199, Issue 1, 15 May 2008, Pages 315–333
Journal: Applied Mathematics and Computation - Volume 199, Issue 1, 15 May 2008, Pages 315–333
نویسندگان
Roderick V.N. Melnik,