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Classically, action-potential-based learning paradigms such as the Bienenstock-Cooper-Munroe (BCM) rule for pulse rates or spike timing-dependent plasticity for pulse pairings have been experimentally demonstrated to evoke long-lasting synaptic weight changes (i.e., plasticity). However, several recent experiments have shown that plasticity also depends on(More)
Memristive devices present a new device technology allowing for the realization of compact non-volatile memories. Some of them are already in the process of industrialization. Additionally, they exhibit complex multilevel and plastic behaviors, which make them good candidates for the implementation of artificial synapses in neuromorphic engineering.(More)
— The computational function of neural networks is thought to depend primarily on the learning/plasticity function carried out at the synapse. Neuromorphic circuit realizations have taken this into account by implementing a variety of synaptical processing functions, with most recent synapse circuits replicating some form of Spike Time Dependent Plasticity(More)
In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from(More)
Memristive devices have recently been proposed as efficient implementations of plastic synapses in neuromorphic systems. The plasticity in these memristive devices , i.e. their resistance change, is defined by the applied waveforms. This behavior resembles biological synapses, whose plasticity is also triggered by mechanisms that are determined by local(More)
—Low-energy Ar + ion irradiation has been applied to an Au/BiFeO 3 /Pt capacitor structure before deposition of the Au top electrode. The irradiated thin film exhibits multilevel resistive switching (RS) without detrimental resistance degradation, which makes the intermediate resistance states more distinguishable, as compared with the nonirradiated thin(More)
  • S Henker, C Mayr, J.-U Schlüßler, R Schüffny, U Ramacher, A Heittmann
  • 2007
Image sensors using 90nm and 65nm CMOS technology were developed, exhibiting characteristics competitive with commercial sensors in conventional technologies. New pixel configurations with stacked photodiodes and high fill factor have been evaluated. Image sensors in deep-submicron can take full advantage of the technology shrink for digital image(More)
A switched-capacitor (SC) neuromorphic system for closed-loop neural coupling in 28 nm CMOS is presented, occupying 600 um by 600 um. It offers 128 input channels (i.e., presynaptic terminals), 8192 synapses and 64 output channels (i.e., neurons). Biologically realistic neuron and synapse dynamics are achieved via a faithful translation of the behavioural(More)
State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The(More)