6,273 research outputs found

    SIRENA: A CAD environment for behavioural modelling and simulation of VLSI cellular neural network chips

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    This paper presents SIRENA, a CAD environment for the simulation and modelling of mixed-signal VLSI parallel processing chips based on cellular neural networks. SIRENA includes capabilities for: (a) the description of nominal and non-ideal operation of CNN analogue circuitry at the behavioural level; (b) performing realistic simulations of the transient evolution of physical CNNs including deviations due to second-order effects of the hardware; and, (c) evaluating sensitivity figures, and realize noise and Monte Carlo simulations in the time domain. These capabilities portray SIRENA as better suited for CNN chip development than algorithmic simulation packages (such as OpenSimulator, Sesame) or conventional neural networks simulators (RCS, GENESIS, SFINX), which are not oriented to the evaluation of hardware non-idealities. As compared to conventional electrical simulators (such as HSPICE or ELDO-FAS), SIRENA provides easier modelling of the hardware parasitics, a significant reduction in computation time, and similar accuracy levels. Consequently, iteration during the design procedure becomes possible, supporting decision making regarding design strategies and dimensioning. SIRENA has been developed using object-oriented programming techniques in C, and currently runs under the UNIX operating system and X-Windows framework. It employs a dedicated high-level hardware description language: DECEL, fitted to the description of non-idealities arising in CNN hardware. This language has been developed aiming generality, in the sense of making no restrictions on the network models that can be implemented. SIRENA is highly modular and composed of independent tools. This simplifies future expansions and improvements.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0

    Tourism and Simulacrum: The Computational Economy of Algorithmic Destinations

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    AbstractThe paper establishes a conceptual and methodological link between destinations and simulacrum through gamified tourism. As a paradigm, gamified tourism provides a rationale and a setting within which to apply computational economics to tourism, an approach amounting to tourism computability. Algorithmic destinations serve as “petri dishes” for real destinations. Utilizing rule sets that embody destination growth dynamics and visitor behavioural norms, seeding points in a cellular automata model (CA) were grown into algorithmic destinations. This is followed by a morphological transformation of geo-tagged satellite images into spatial points. The overlap of this additive and subtractive approach is at the core of tourism computability. Finally, the spatio-temporal dynamics of economic resilience was traced out through a visual phenomenology of algorithmic destinations. The gamification of tourism should be embraced as it holds up a flicker of hope for mature destinations, amidst the onset of museumification and increased commoditization of heritage sites. Gamification is treated as part of the reflexive cycle for destination authenticity; a notion that that Cohen (1988) alluded to in his discussion of emergent authenticity in destination image formation. Seen in this light, the museumification of Venice and the proliferation of its simulacrum, such as the Venetian Hotel in Macao and Venice-themed hotels across the globe, are prefigures and archetypes of a glorious age of gamified tourism

    Circuit Design Using VHDL Language Transformations

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