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The device can be switched off by applying the opposite voltage, which drives the oxygen back into the first layer. The amount of resistance can be controlled by varying how long the voltage is applied.

The memristor’s electronic properties have led the HP researchers to pursue two potential applications for the device. One is employing it for nonvolatile memory similar to the flash memory used now in digital cameras and cell phones. The speed of memristors suggests that they could be far faster than flash memory and phase-change memory, another type of nonvolatile memory being developed now by Intel and others as a replacement for flash. And the simple devices can be packed densely, potentially allowing memristor chips to store more data than flash memory. Since HP doesn’t make computer chips, the company will likely license the technology to another company.

HP researchers are also making memristor-based chips that mimic the workings of neural networks in the brain. During learning, the connections between neurons in the brain change, some becoming stronger and others weaker over time. The strength of these connections can have a range of different values. It’s possible to simulate this range by making circuits of many transistors. But this can take a large number of transistors. Williams says that it’s possible to do the same thing with just one memristor, since it can be set to have a range of different resistance levels. That could reduce the size of such neural networks by 10,000 times, he says.

Williams envisions a system that uses transistors for the role of neurons, and memristors for the connections between them. Such a memristor-based system would be smaller and use much less energy than one built of transistors alone. Since it would have the ability to adapt in much the same way that brains adapt, it could be good at tasks, such as speech recognition, that are easy for animals but difficult for computers. The HP researchers hope to have prototypes of such chips by next year.

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Credit: J. J. Yang, HP Labs

Tagged: Computing, brain, memory, HP, neuron, neural network, memristor, synapse

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