Memristor Emulation for Signal Processing Applications
- Master/Diploma Thesis
- Announcement date
- 12 Jan 2011
- Matthias Leeb
- Research Areas
A Memristor is a two-terminal circuit element that may fundamentally change the way information is processed in future signal processing systems. The Memristor can be understood as a resistor whose resistance can be programmed. It therefore combines a memory element that can be programmed with a conventional resistor. How can we use this for signal processing? The memory can be used to store information, while the resistor performs multiplication and division operations - just consider the simple equation of Ohm’s law.
Memristors - although originally conceived in the 1970s - have only recently gained broad interest in the scientific community. This is because it has been realized that memristive effects are a possibility to explain the strange electrical behavior of nanoscale electronic devices.
Memristors are not yet available for experimentation. Goal of this project is to EMULATE a memristor in a flexible way. The storage and controllable resistor will be realized in separate devices, namely a simple microcontroller including an ADC and a tunable resistor. With this emulator, we will be able to reproduce the memristive properties reported in the recent literature on memristive nanoscale circuits.
The project can be extended to an MSc Thesis, where the student could investigate signal processing applications enabled by memristive devices.
Matthias Leeb already finished his master project on this topic. You can find his report here.
- Design and build the memristor emulator using microcontrollers and programmable resistors
- Program the microcontroller to reproduce memristor properties
- Demonstrate the memristive properties in lab
- Some (limited) experience in electronic circuit design using microcontrollers is desired, but this experience can also be gained through this project!
Klaus Witrisal (firstname.lastname@example.org or 0316/873 4431)
 Y. V. Pershin and M. Di Ventra, “Experimental demonstration of associative memory with memristive neural networks,” Neural Networks, 2010.
 D. B. Strukov, G. S. Snider, D. R. Stewart, and R. S. Williams, “The missing memristor found,” Nature, 2008.
 K. Witrisal, “A Memristor-Based Stored-Reference Receiver-The UWB Solution?” IET Electronics Letters, 2009.