2,448 research outputs found

    Long-range temporal correlations in scale-free neuromorphic networks

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    © 2020 Massachusetts Institute of Technology. Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing

    Atomic Scale Dynamics Drive Brain-like Avalanches in Percolating Nanostructured Networks.

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    Self-assembled networks of nanoparticles and nanowires have recently emerged as promising systems for brain-like computation. Here, we focus on percolating networks of nanoparticles which exhibit brain-like dynamics. We use a combination of experiments and simulations to show that the brain-like network dynamics emerge from atomic-scale switching dynamics inside tunnel gaps that are distributed throughout the network. The atomic-scale dynamics emulate leaky integrate and fire (LIF) mechanisms in biological neurons, leading to the generation of critical avalanches of signals. These avalanches are quantitatively the same as those observed in cortical tissue and are signatures of the correlations that are required for computation. We show that the avalanches are associated with dynamical restructuring of the networks which self-tune to balanced states consistent with self-organized criticality. Our simulations allow visualization of the network states and detailed mechanisms of signal propagation

    Simultaneous storage of medical images in the spatial and frequency domain: A comparative study

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    BACKGROUND: Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. METHODS: The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. RESULTS: It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. CONCLUSION: The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient

    Modulation of Sn concentration in ZnO nanorod array: intensification on the conductivity and humidity sensing properties

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    Tin (Sn)-doped zinc oxide (ZnO) nanorod arrays (TZO) were synthesized onto aluminum-doped ZnO-coated glass substrate via a facile sonicated sol–gel immersion method for humidity sensor applications. These nanorod arrays were grown at different Sn concentrations ranging from 0.6 to 3 at.%. X-ray diffraction patterns showed that the deposited TZO arrays exhibited a wurtzite structure. The stress/strain condition of the ZnO film metamorphosed from tensile strain/compressive stress to compressive strain/tensile stress when the Sn concentrations increased. Results indicated that 1 at.% Sn doping of TZO, which has the lowest tensile stress of 0.14 GPa, generated the highest conductivity of 1.31 S cm− 1. In addition, 1 at.% Sn doping of TZO possessed superior sensitivity to a humidity of 3.36. These results revealed that the optimum performance of a humidity-sensing device can be obtained mainly by controlling the amount of extrinsic element in a ZnO film

    Physics Potential of the ICAL detector at the India-based Neutrino Observatory (INO)

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    The upcoming 50 kt magnetized iron calorimeter (ICAL) detector at the India-based Neutrino Observatory (INO) is designed to study the atmospheric neutrinos and antineutrinos separately over a wide range of energies and path lengths. The primary focus of this experiment is to explore the Earth matter effects by observing the energy and zenith angle dependence of the atmospheric neutrinos in the multi-GeV range. This study will be crucial to address some of the outstanding issues in neutrino oscillation physics, including the fundamental issue of neutrino mass hierarchy. In this document, we present the physics potential of the detector as obtained from realistic detector simulations. We describe the simulation framework, the neutrino interactions in the detector, and the expected response of the detector to particles traversing it. The ICAL detector can determine the energy and direction of the muons to a high precision, and in addition, its sensitivity to multi-GeV hadrons increases its physics reach substantially. Its charge identification capability, and hence its ability to distinguish neutrinos from antineutrinos, makes it an efficient detector for determining the neutrino mass hierarchy. In this report, we outline the analyses carried out for the determination of neutrino mass hierarchy and precision measurements of atmospheric neutrino mixing parameters at ICAL, and give the expected physics reach of the detector with 10 years of runtime. We also explore the potential of ICAL for probing new physics scenarios like CPT violation and the presence of magnetic monopoles.Comment: 139 pages, Physics White Paper of the ICAL (INO) Collaboration, Contents identical with the version published in Pramana - J. Physic
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