The Memristor Discovery platform is designed for a general introduction to memristor electronics that helps students avoid many of the common pitfalls of working with memristors for the first time. The board accepts 1X16 Linear Array chips and enables unitary (mode 1) or differential (mode 2) access to the 16 memristors on the chip. The board plugs into the Digilent Analog Discovery 2 or 3, not included, and runs the open source Memristor Discovery software.
This Package Includes:
- One 1X16 array memristor chip
- Cross-platform software (Mac, Windows 10, Linux)
- 60 page user manual provided on a USB drive.
Detailed User Manual
A detailed manual guides users from start to finish, from workstation setup, AD2 Calibration, Software Installation, Memristor experiments, Pro-Tips and more. Ideal for class labs or independent study. Read Preview.
Open Source & Extensible Software
Software for the Memristor Discovery V2 board is open-source and available at the project GitHub page. The Memristor Discovery app runs on the latest versions of MacOS, Debian-based Linux and Windows 10. Requires the Digilent waveforms Framework to be installed on your system.
|Drive a memristor in series with a resistor with a sinusoidal or triangle waveform and observe the response as either a time series, I-V or G-V plot, revealing the signature hysteresis behavior of the memristor. The user can adjust the input signal voltage, frequency and offset and observe the response in real-time.
|Drive a memristor in series with a resistor with various ramping functions including sawtooth, sawtoothupdown, triangle and triangleupdown at time scale from 10 to 1000ms.
|Drive a memristor in series with a resistor with one or more tunable pulse waveforms ( Square, Sine, Triangle, etc) and observe the instantaneous and post-pulse response.
Shelf Life Experiment
|Used to measure the switching function of memristors over very long durations of time, recording the measured data into a CSV text file at specified intervals.
|Allows you to drive 8 differential synapses with elemental kT-RAM instructions and observe a continuous response in synaptic state and synaptic pair conductances via repeated read instructions.
|Performs online-learning supervised classification with an eight synapse memristor neuron.