1,588 research outputs found

    Image Segmentation Using Frequency Locking of Coupled Oscillators

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    Synchronization of coupled oscillators is observed at multiple levels of neural systems, and has been shown to play an important function in visual perception. We propose a computing system based on locally coupled oscillator networks for image segmentation. The system can serve as the preprocessing front-end of an image processing pipeline where the common frequencies of clusters of oscillators reflect the segmentation results. To demonstrate the feasibility of our design, the system is simulated and tested on a human face image dataset and its performance is compared with traditional intensity threshold based algorithms. Our system shows both better performance and higher noise tolerance than traditional methods.Comment: 7 pages, 14 figures, the 51th Design Automation Conference 2014, Work in Progress Poster Sessio

    VLSI neural networks for computer vision

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    Linear Operation of Switch-Mode Outphasing Power Amplifiers

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    Radio transceivers are playing an increasingly important role in modern society. The ”connected” lifestyle has been enabled by modern wireless communications. The demand that has been placed on current wireless and cellular infrastructure requires increased spectral efficiency however this has come at the cost of power efficiency. This work investigates methods of improving wireless transceiver efficiency by enabling more efficient power amplifier architectures, specifically examining the role of switch-mode power amplifiers in macro cell scenarios. Our research focuses on the mechanisms within outphasing power amplifiers which prevent linear amplification. From the analysis it was clear that high power non-linear effects are correctable with currently available techniques however non-linear effects around the zero crossing point are not. As a result signal processing techniques for suppressing and avoiding non-linear operation in low power regions are explored. A novel method of digital pre-distortion is presented, and conventional techniques for linearisation are adapted for the particular needs of the outphasing power amplifier. More unconventional signal processing techniques are presented to aid linearisation of the outphasing power amplifier, both zero crossing and bandwidth expansion reduction methods are designed to avoid operation in nonlinear regions of the amplifiers. In combination with digital pre-distortion the techniques will improve linearisation efforts on outphasing systems with dynamic range and bandwidth constraints respectively. Our collaboration with NXP provided access to a digital outphasing power amplifier, enabling empirical analysis of non-linear behaviour and comparative analysis of behavioural modelling and linearisation efforts. The collaboration resulted in a bench mark for linear wideband operation of a digital outphasing power amplifier. The complimentary linearisation techniques, bandwidth expansion reduction and zero crossing reduction have been evaluated in both simulated and practical outphasing test benches. Initial results are promising and indicate that the benefits they provide are not limited to the outphasing amplifier architecture alone. Overall this thesis presents innovative analysis of the distortion mechanisms of the outphasing power amplifier, highlighting the sensitivity of the system to environmental effects. Practical and novel linearisation techniques are presented, with a focus on enabling wide band operation for modern communications standards

    On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing

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    In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits and system level techniques. The convolution processing is based on the address–event-representation (AER) technique, which is a spike-based biologically inspired image and video representation technique that favors communication bandwidth for pixels with more information. As a first test prototype, a pixel array of 16x16 has been implemented with programmable kernel size of up to 16x16. The chip has been fabricated in a standard 0.35- m complimentary metal–oxide–semiconductor (CMOS) process. The technique also allows to process larger size images by assembling 2-D arrays of such chips. Pixel operation exploits low-power mixed analog–digital circuit techniques. Because of the low currents involved (down to nanoamperes or even picoamperes), an important amount of pixel area is devoted to mismatch calibration. The rest of the chip uses digital circuit techniques, both synchronous and asynchronous. The fabricated chip has been thoroughly tested, both at the pixel level and at the system level. Specific computer interfaces have been developed for generating AER streams from conventional computers and feeding them as inputs to the convolution chip, and for grabbing AER streams coming out of the convolution chip and storing and analyzing them on computers. Extensive experimental results are provided. At the end of this paper, we provide discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems.Commission of the European Communities IST-2001-34124 (CAVIAR)Commission of the European Communities 216777 (NABAB)Ministerio de Educación y Ciencia TIC-2000-0406-P4Ministerio de Educación y Ciencia TIC-2003-08164-C03-01Ministerio de Educación y Ciencia TEC2006-11730-C03-01Junta de Andalucía TIC-141

    Shaping bacterial population behavior through computer-interfaced control of individual cells

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    This is the final version. Available from Springer Nature via the DOI in this record.Strains and data are available from the authors upon request. Custom scripts for the described setup are available as Supplementary Software.Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.European Union's Seventh Frame ProgrammeAustrian Science FundAgence Nationale de la RechercheAgence Nationale de la RechercheAgence Nationale de la Recherch

    Doppler Radar Techniques for Distinct Respiratory Pattern Recognition and Subject Identification.

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    Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017
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