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Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 10(14) synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with(More)
Information and communication technology (ICT) is now calling for solutions enabling lower power consumption, further miniaturization, and multifunctionality requiring the development of new device concepts and new materials. [ 1 ] One of the most fertile approaches to meet such demands is spintronics, which is now facing the challenge of evolving from the(More)
Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses - the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses ("spikes")(More)
Nanoparticles (NPs) embedded in a conductive or insulating matrix play a key role in memristors and in flash memory devices. However, the role of proximity to the interface of isolated NPs has never been directly observed nor fully understood. Here we show that a reversible local switching in tunnel conductivity can be achieved by applying an appropriate(More)
b) c) Top Electrode Bottom Electrode Top domains Bottom domains Middle Domain a) Co LSMO Co LSMO Low Resistance High resistance The Fig.4a shows the spin valve presented previously in Fig.1 before any higher voltage was applied-this corresponds to the lowest resistance state and a SVMR of 22%. Next, we apply a voltage bias of-1.5 V and the device resistance(More)
Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore's law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applications.(More)
We have designed, fabricated, and successfully tested a prototype mixed-signal, 28×28-binary-input, 10-ouput, 3-layer neuromorphic network (" MLP perceptron "). It is based on embedded nonvolatile floating-gate cell arrays redesigned from a commercial 180-nm NOR flash memory. The arrays allow precise (~1%) individual tuning of all memory cells, having(More)
We experimentally demonstrate classification of 4×4 binary images into 4 classes, using a 3-layer mixed-signal neuromorphic network (" MLP perceptron "), based on two passive 20×20 memristive crossbar arrays, board-integrated with discrete CMOS components. The network features 10 hidden-layer and 4 output-layer analog CMOS neurons and 428 metal-oxide(More)
The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information technology. The main idea of such primitives is to employ instance-specific process-induced variations in electronic hardware as a source of cryptographic data. Among the emergent(More)