Reconfigurable DAC implemented by memristor based neural network

This device is a digital-to-analog converter that uses a neural network to transform digital input signals into an analog output. The neural network is configured to perform this conversion, and its internal connections are adjusted through a learning process, specifically using a method called stochastic gradient descent, to minimize conversion errors.

Why it matters: Since 2018, advancements in memristor fabrication and neuromorphic hardware design have made the practical implementation of specialized neural network circuits more feasible. This could enable more compact and energy-efficient DACs.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedMemristor hardware, custom silicon, neural network

3 AI reinvention directions for this patent

See all three

AI gives you a few directions you could take this. Pick one, and we check whether your version is different enough to patent, then write the filing.

Reinvent this with AI

Where this one came from

Every morning we go through millions of abandoned patents and pick out 15 worth your time. This was one of today’s.

This one

+10