82 research outputs found

    Cellular automata with complicated dynamics

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    A subshift is a collection of bi-infinite sequences (configurations) of symbols where some finite patterns of symbols are forbidden to occur. A cellular automaton is a transformation that changes each configuration of a subshift into another one by using a finite look-up table that tells how any symbol occurring at any possible context is to be changed. A cellular automaton can be applied repeatedly on the configurations of the subshift, thus making it a dynamical system. This thesis focuses on cellular automata with complex dynamical behavior, with some different definitions of the word “complex”. First we consider a naturally occurring class of cellular automata that we call multiplication automata and we present a case study with the point of view of symbolic, topological and measurable dynamics. We also present an application of these automata to a generalized version of Mahler’s problem. For different notions of complex behavior one may also ask whether a given subshift or class of subshifts has a cellular automaton that presents this behavior. We show that in the class of full shifts the Lyapunov exponents of a given reversible cellular automaton are uncomputable. This means that in the dynamics of reversible cellular automata the long term maximal propagation speed of a perturbation made in an initial configuration cannot be determined in general from short term observations. In the last part we construct, on all mixing sofic shifts, diffusive glider cellular automata that can decompose any finite configuration into two distinct components that shift into opposing direction under repeated action of the automaton. This implies that every mixing sofic shift has a reversible cellular automaton all of whose directions are sensitive in the sense of the definition of Sablik. We contrast this by presenting a family of synchronizing subshifts on which all reversible cellular automata always have a nonsensitive direction

    A CNN based hybrid approach towards automatic image registration

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    Image registration is a key component of spatial analyses that involve different data sets of the same area. Automatic approaches in this domain have witnessed the application of several intelligent methodologies over the past decade; however accuracy of these approaches have been limited due to the inability to properly model shape as well as contextual information. In this paper, we investigate the possibility of an evolutionary computing based framework towards automatic image registration. Cellular Neural Network has been found to be effective in improving feature matching as well as resampling stages of registration, and complexity of the approach has been considerably reduced using corset optimization. CNN-prolog based approach has been adopted to dynamically use spectral and spatial information for representing contextual knowledge. The salient features of this work are feature point optimisation, adaptive resampling and intelligent object modelling. Investigations over various satellite images revealed that considerable success has been achieved with the procedure. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling

    SIGNAL PROCESSING TECHNIQUES AND APPLICATIONS

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    As the technologies scaling down, more transistors can be fabricated into the same area, which enables the integration of many components into the same substrate, referred to as system-on-chip (SoC). The components on SoC are connected by on-chip global interconnects. It has been shown in the recent International Technology Roadmap of Semiconductors (ITRS) that when scaling down, gate delay decreases, but global interconnect delay increases due to crosstalk. The interconnect delay has become a bottleneck of the overall system performance. Many techniques have been proposed to address crosstalk, such as shielding, buffer insertion, and crosstalk avoidance codes (CACs). The CAC is a promising technique due to its good crosstalk reduction, less power consumption and lower area. In this dissertation, I will present analytical delay models for on-chip interconnects with improved accuracy. This enables us to have a more accurate control of delays for transition patterns and lead to a more efficient CAC, whose worst-case delay is 30-40% smaller than the best of previously proposed CACs. As the clock frequency approaches multi-gigahertz, the parasitic inductance of on-chip interconnects has become significant and its detrimental effects, including increased delay, voltage overshoots and undershoots, and increased crosstalk noise, cannot be ignored. We introduce new CACs to address both capacitive and inductive couplings simultaneously.Quantum computers are more powerful in solving some NP problems than the classical computers. However, quantum computers suffer greatly from unwanted interactions with environment. Quantum error correction codes (QECCs) are needed to protect quantum information against noise and decoherence. Given their good error-correcting performance, it is desirable to adapt existing iterative decoding algorithms of LDPC codes to obtain LDPC-based QECCs. Several QECCs based on nonbinary LDPC codes have been proposed with a much better error-correcting performance than existing quantum codes over a qubit channel. In this dissertation, I will present stabilizer codes based on nonbinary QC-LDPC codes for qubit channels. The results will confirm the observation that QECCs based on nonbinary LDPC codes appear to achieve better performance than QECCs based on binary LDPC codes.As the technologies scaling down further to nanoscale, CMOS devices suffer greatly from the quantum mechanical effects. Some emerging nano devices, such as resonant tunneling diodes (RTDs), quantum cellular automata (QCA), and single electron transistors (SETs), have no such issues and are promising candidates to replace the traditional CMOS devices. Threshold gate, which can implement complex Boolean functions within a single gate, can be easily realized with these devices. Several applications dealing with real-valued signals have already been realized using nanotechnology based threshold gates. Unfortunately, the applications using finite fields, such as error correcting coding and cryptography, have not been realized using nanotechnology. The main obstacle is that they require a great number of exclusive-ORs (XORs), which cannot be realized in a single threshold gate. Besides, the fan-in of a threshold gate in RTD nanotechnology needs to be bounded for both reliability and performance purpose. In this dissertation, I will present a majority-class threshold architecture of XORs with bounded fan-in, and compare it with a Boolean-class architecture. I will show an application of the proposed XORs for the finite field multiplications. The analysis results will show that the majority class outperforms the Boolean class architectures in terms of hardware complexity and latency. I will also introduce a sort-and-search algorithm, which can be used for implementations of any symmetric functions. Since XOR is a special symmetric function, it can be implemented via the sort-and-search algorithm. To leverage the power of multi-input threshold functions, I generalize the previously proposed sort-and-search algorithm from a fan-in of two to arbitrary fan-ins, and propose an architecture of multi-input XORs with bounded fan-ins

    Cellular Automata

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    Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

    Proceedings of AUTOMATA 2010: 16th International workshop on cellular automata and discrete complex systems

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    International audienceThese local proceedings hold the papers of two catgeories: (a) Short, non-reviewed papers (b) Full paper
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