248 research outputs found

    Investigation of vertical cavity surface emitting laser dynamics for neuromorphic photonic systems

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    We report an approach based upon vertical cavity surface emitting lasers (VCSELs) to reproduce optically different behaviors exhibited by biological neurons but on a much faster timescale. The technique proposed is based on the polarization switching and nonlinear dynamics induced in a single VCSEL under polarized optical injection. The particular attributes of VCSELs and the simple experimental configuration used in this work offer prospects of fast, reconfigurable processing elements with excellent fan-out and scaling potentials for use in future computational paradigms and artificial neural networks. © 2012 American Institute of Physics

    Extended SNP Systems with States

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    We consider (extended) spiking neural P systems with states, where the applicability of rules in a neuron not only depends on the presence of su ciently many spikes (yet in contrast to the standard de nition, no regular checking sets are used), but also on the current state of the neuron. Moreover, a spiking rule not only sends spikes, but also state information to the connected neurons. We prove that this variant of the original model of extended spiking neural P systems can simulate register machines with only two states, even in the basic non-extended variant

    Controllable spiking patterns in long-wavelength VCSELs for neuromorphic photonics systems

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    Multiple controllable spiking patterns are obtained in a 1310 nm Vertical Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely parallel and orthogonal. Achievement of reproducible spiking responses in VCSELs operating at the telecom wavelengths offers great promise for future uses of these devices in ultrafast neuromorphic photonic systems for non-traditional computing applications.Comment: 10 pages, 6 figures, journal submissio

    Solving SAT with Antimatter in Membrane Computing

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    The set of NP-complete problems is split into weakly and strongly NP- complete ones. The di erence consists in the in uence of the encoding scheme of the input. In the case of weakly NP-complete problems, the intractability depends on the encoding scheme, whereas in the case of strongly NP-complete problems the problem is intractable even if all data are encoded in a unary way. The reference for strongly NP-complete problems is the Satis ability Problem (the SAT problem). In this paper, we provide a uniform family of P systems with active membranes which solves SAT { without polarizations, without dissolution, with division for elementary membranes and with matter/antimatter annihilation. To the best of our knowledge, it is the rst solution to a strongly NP-complete problem in this P system model.Ministerio de Economía y Competitividad TIN2012-3743

    Some Open Problems Collected During 7th BWMC

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    A few open problems and research topics collected during the 7th Brain- storming Week on Membrane Computing are briefly presented; further details can be found in the papers included in the volume.Junta de Andalucía P08 – TIC 0420

    Chaotic Phase Synchronization in Bursting-neuron Models Driven by a Weak Periodic Force

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    We investigate the entrainment of a neuron model exhibiting a chaotic spiking-bursting behavior in response to a weak periodic force. This model exhibits two types of oscillations with different characteristic time scales, namely, long and short time scales. Several types of phase synchronization are observed, such as 1 : 1 phase locking between a single spike and one period of the force and 1 : l phase locking between the period of slow oscillation underlying bursts and l periods of the force. Moreover, spiking-bursting oscillations with chaotic firing patterns can be synchronized with the periodic force. Such a type of phase synchronization is detected from the position of a set of points on a unit circle, which is determined by the phase of the periodic force at each spiking time. We show that this detection method is effective for a system with multiple time scales. Owing to the existence of both the short and the long time scales, two characteristic phenomena are found around the transition point to chaotic phase synchronization. One phenomenon shows that the average time interval between successive phase slips exhibits a power-law scaling against the driving force strength and that the scaling exponent has an unsmooth dependence on the changes in the driving force strength. The other phenomenon shows that Kuramoto's order parameter before the transition exhibits stepwise behavior as a function of the driving force strength, contrary to the smooth transition in a model with a single time scale
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