1,343 research outputs found

    Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

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    A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

    A CMOS Spiking Neuron for Dense Memristor-Synapse Connectivity for Brain-Inspired Computing

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    Neuromorphic systems that densely integrate CMOS spiking neurons and nano-scale memristor synapses open a new avenue of brain-inspired computing. Existing silicon neurons have molded neural biophysical dynamics but are incompatible with memristor synapses, or used extra training circuitry thus eliminating much of the density advantages gained by using memristors, or were energy inefficient. Here we describe a novel CMOS spiking leaky integrate-and-fire neuron circuit. Building on a reconfigurable architecture with a single opamp, the described neuron accommodates a large number of memristor synapses, and enables online spike timing dependent plasticity (STDP) learning with optimized power consumption. Simulation results of an 180nm CMOS design showed 97% power efficiency metric when realizing STDP learning in 10,000 memristor synapses with a nominal 1M{\Omega} memristance, and only 13{\mu}A current consumption when integrating input spikes. Therefore, the described CMOS neuron contributes a generalized building block for large-scale brain-inspired neuromorphic systems.Comment: This is a preprint of an article accepted for publication in International Joint Conference on Neural Networks (IJCNN) 201

    Deciphering the microbial ecology in bio- gas reactors for optimizing the anaerobic digestion process

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    A CMOS Spiking Neuron for Brain-Inspired Neural Networks with Resistive Synapses and In-Situ Learning

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    Nanoscale resistive memories are expected to fuel dense integration of electronic synapses for large-scale neuromorphic system. To realize such a brain-inspired computing chip, a compact CMOS spiking neuron that performs in-situ learning and computing while driving a large number of resistive synapses is desired. This work presents a novel leaky integrate-and-fire neuron design which implements the dual-mode operation of current integration and synaptic drive, with a single opamp and enables in-situ learning with crossbar resistive synapses. The proposed design was implemented in a 0.18 μ\mum CMOS technology. Measurements show neuron's ability to drive a thousand resistive synapses, and demonstrate an in-situ associative learning. The neuron circuit occupies a small area of 0.01 mm2^2 and has an energy-efficiency of 9.3 pJ//spike//synapse

    Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies

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    In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon

    Swift Monitoring Observations of Mrk 231: Detection of Ultraviolet Variability

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    We analyze 168 Swift monitoring observations of the nearest broad absorption line quasar Mrk 231 in the UV and X-ray bands, where we detect significant variability in the UV (∼\sim2246\AA) light curve with a null probability of 4.3×10−104.3\times10^{-10} for a constant model. Separately, from an archival sample of Swift observed active galactic nuclei (AGN), we measure the relation between UV excess variance and luminosity, finding that the normalized UV excess variance decreases with luminosity. Comparing to this mean relation, the normalized UV excess variance of Mrk 231 is smaller, however within the scatter characterising the full population. The upper limit of the X-ray excess variance is consistent with other AGN. The power spectrum density of the UV light curve can be well fit by a power law model with a slope of 1.82±0.141.82\pm0.14 between 10−7.510^{-7.5} and 10−610^{-6} Hz, consistent with those for typical AGN, with no obvious quasi-periodical oscillation peaks. The UV variability and its power spectrum suggest that a significant amount of the UV emission of Mrk 231 is from the accretion disk. The consistencies in the normalized UV variability and the shape of the power spectrum density between Mrk 231 and other normal AGN suggest that the origin of UV variability of broad absorption line quasars is similar to other AGN, and dust scattering at large scales such as the torus is not a dominating process for the UV emission of Mrk 231. Significant scattering, if present, is constrained to smaller than ∼\sim10 light days. We perform lagged correlation analysis between the UV and X-ray light curves and find the correlation insignificant within the present data.Comment: 8 pages, 4 figures, accepted by MNRA

    Reflective liquid crystal projection displays with low voltage and high contrast using improved bisector effect.

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    Methods, systems, devices and apparatus of using a reflective liquid crystal device for projection display operating at a reduced driving voltage and having an increased contrast ratio are disclosed. The reflective liquid crystal device comprises a first substrate, a second substrate with reflector means, and a twisted nematic liquid crystal layer between the first substrate and the second substrate. A polarizing beam splitter is placed outside of the reflective liquid crystal device and adjacent to the first substrate. By setting the entrance polarization direction of the polarizing beam splitter along the azimuthal angle of the linearly polarized eigenmode of the reflective liquid crystal device at the designed driving voltage, a perfect dark state is obtained, which leads to a high contrast ratio at the designed low driving voltage
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