Probabilistic Cellular Automata

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Around probabilistic cellular automata

We survey probabilistic cellular automata with approaches coming from combinatorics, statistical physics, and theoretical computer science, each bringing a different viewpoint. Some of the questions studied are specific to a domain, and some others are shared, most notably the ergodicity problem.

متن کامل

Probabilistic Cellular Automata

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involve...

متن کامل

Computing with Probabilistic Cellular Automata

We investigate the computational capabilities of probabilistic cellular automata by means of the density classification problem. We find that a specific probabilistic cellular automata rule is able to solve the density classification problem, i.e. classifies binary input strings according to the number of 1’s and 0’s in the string, and show that its computational abilities are related to critic...

متن کامل

Identification of probabilistic cellular automata

The identification of probabilistic cellular automata (PCA) is studied using a new two stage neighborhood detection algorithm. It is shown that a binary probabilistic cellular automaton (BPCA) can be described by an integer-parameterized polynomial corrupted by noise. Searching for the correct neighborhood of a BPCA is then equivalent to selecting the correct terms which constitute the polynomi...

متن کامل

Statistical Mechanics of Probabilistic Cellular Automata

We investigate the behavior of discrete-time probabilistic cellular automata (PCA), which are Markov processes on spin configurations on a d-dimensional lattice, from a rigorous statistical mechanics point of view. In particular, we exploit, whenever possible, the correspondence between stationary measures on the space-time histories of PCAs on 77 a and translation-invariant Gibbs states for a ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Computational Biology

سال: 2014

ISSN: 1066-5277,1557-8666

DOI: 10.1089/cmb.2014.0074