APPLICATION OF ELEMENTARY CELLULAR AUTOMATA TO MUSIC GENERATION

We present a simple music generation algorithm based on periodic pattern from the Elementary Cellular Automata (ECAs). Our algorithm may be regarded as a simplified version of the WolframTones. The simplification is important in systematic application of ECAs to music generation and its evaluation. We propose a simple music generation algorithm. As preparation, we explain the scales and the rhythm used in it. We evaluate some typical musical examples and evaluate their characteristics

Analysis of Cellular Automata with Mixed Rules and its Synthesis

This paper studies the synthesis and the stability of the cellular automata with mixed rules(MCA). Although the dynamics of MCA are determined by rule tables, the number of rule tables is enormous and brute-force search is almost impossible. We propose three synthesis methods based on the genetic algorithm (GA) which is related to the stability.First, we analyze the stability of the teacher signal which is a periodic control signal of AC/DC converter. The fitness of GA is the local stability of the teacher signal.Second, there are several isolated spatiotemporal patterns without transient phenomena by using the elementary cellular automata (ECA). We analyze the stability of those patterns by using MCA and GA. The fitness of GA is the global stability of an isolated pattern.Finally, there are only isolated spatiotemporal patterns without transient phenomena by using ECA. We synthesize those patterns and analyze the stability. The fitness of GA is the number of times to enlarge transient states for steady states.修士(工学)法政大学 (Hosei University

ANALYSIS AND APPLICATION OF CELLULAR AUTOMATA WITH TIME-VARIANT RULES

The elementary cellular automata (ECAs) is a digital dynamical system in which time, space and states are all discrete. Depending on a rule, the ECAs can exhibit a variety of spatiotemporal patterns. In this paper, we present time-variant rule elementary cellular automata (TCAs). In order to analyze the TCAs, we introduce three simple feature quantities. The feature quantities shows expression ability, error rate and stability. Using the feature quantities, we investigate typical TCAs in numerical experiments

A parallel block-based encryption schema for digital images using reversible cellular automata

AbstractWe propose a novel images encryption schema based on reversible one-dimensional cellular automata. Contrasting to the sequential operating mode of several existing approaches, the proposed one is fully parallelizable since the encryption/decryption tasks can be executed using multiple processes running independently for the same single image. The parallelization is made possible by defining a new RCA-based construction of an extended pseudorandom permutation that takes a nonce as a supplementary parameter. The defined PRP exploit the chaotic behavior and the high initial condition's sensitivity of the RCAs to ensure perfect cryptographic security properties. Results of various experiments and analysis show that high security and execution performances can be achieved using the approach, and furthermore, it provides the ability to perform a selective area decryption since any part of the ciphered-image can be deciphered independently from others, which is very useful for real time applications

A Survey of Cellular Automata: Types, Dynamics, Non-uniformity and Applications

Cellular automata (CAs) are dynamical systems which exhibit complex global behavior from simple local interaction and computation. Since the inception of cellular automaton (CA) by von Neumann in 1950s, it has attracted the attention of several researchers over various backgrounds and fields for modelling different physical, natural as well as real-life phenomena. Classically, CAs are uniform. However, non-uniformity has also been introduced in update pattern, lattice structure, neighborhood dependency and local rule. In this survey, we tour to the various types of CAs introduced till date, the different characterization tools, the global behaviors of CAs, like universality, reversibility, dynamics etc. Special attention is given to non-uniformity in CAs and especially to non-uniform elementary CAs, which have been very useful in solving several real-life problems.Comment: 43 pages; Under review in Natural Computin

Investigations of cellular automata-based stream ciphers

In this thesis paper, we survey the literature arising from Stephan Wolfram\u27s original paper, “Cryptography with Cellular Automata” [WOL86] that first suggested stream ciphers could be constructed with cellular automata. All published research directly and indirectly quoting this paper are summarized up until the present. We also present a novel stream cipher design called Sum4 that is shown to have good randomness properties and resistance to approximation using linear finite shift registers. Sum4 is further studied to determine its effective strength with respect to key size given that an attack with a SAT solver is more efficient than a bruteforce attack. Lastly, we give ideas for further research into improving the Sum4 cipher

Linking Climate Change and Socio-economic Impact for Long-term Urban Growth in Three Mega-cities

Urbanization has become a global trend under the impact of population growth, socio-economic development, and globalization. However, the interactions between climate change and urban growth in the context of economic geography are unclear due to missing links in between the recent planning megacities. This study aims to conduct a multi-temporal change analysis of land use and land cover in New York City, City of London, and Beijing using a cellular automata-based Markov chain model collaborating with fuzzy set theory and multi-criteria evaluation to predict the city\u27s future land use changes for 2030 and 2050 under the background of climate change. To determine future natural forcing impacts on land use in these megacities, the study highlighted the need for integrating spatiotemporal modeling analyses, such as Statistical Downscale Modeling (SDSM) driven by climate change, and geospatial intelligence techniques, such as remote sensing and geographical information system, in support of urban growth assessment. These SDSM findings along with current land use policies and socio-economic impact were included as either factors or constraints in a cellular automata-based Markov Chain model to simulate and predict land use changes in megacities for 2030 and 2050. Urban expansion is expected in these megacities given the assumption of stationarity in urban growth process, although climate change impacts the land use changes and management. More land use protection should be addressed in order to alleviate the impact of climate change