Name
Abstract | ||
|---|---|---|
This paper describes memristor-based neuromorphic circuits for non-linear separable pattern recognition. We initially describe a memristor based neuron circuit and then show how multilayer neural networks can be constructed using this neuron circuit. These neuromorphic circuits are capable of learning both linearly and non-linearly separable logic functions. This paper presents the first study of applying neural network learning algorithms to these circuits in SPICE. Our simulations capture alternate current paths within the memristor crossbars and wire resistances that are essential to properly model in crossbar circuits. Our results show that neural network learning algorithms are able to train around these alternate current paths. Further, it was shown that neural networks can properly train the passive memristor-based crossbars without having to use virtual ground mode operational amplifiers as suggested in previous work. Our circuit requires in-situ training, but reduces the number of transistors required by the circuit by about 3 times and reduced the circuit power consumption almost 2 orders of magnitude compared to a virtual ground approach. The key impact of this study is the demonstration through low level circuit simulations that dense memristor crossbars can be effectively utilized to build neuromorphic processors. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IJCNN.2014.6889807 | Neural Networks |
Keywords | Field | DocType |
SPICE,learning (artificial intelligence),memristors,neural nets,SPICE,crossbar circuits,memristive crossbars,memristor based neuron circuit,memristor-based neuromorphic circuits,multilayer neural networks,neural network learning algorithm,neuromorphic processors,nonlinear separable pattern recognition,nonlinearly separable logic functions,virtual ground approach | Virtual ground,Memristor,Computer science,Neuromorphic engineering,Artificial intelligence,Artificial neural network,Electronic circuit,Transistor,Machine learning,Operational amplifier,Crossbar switch | Conference |
ISSN | Citations | PageRank |
2161-4393 | 1 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chris Yakopcic | 1 | 140 | 13.10 |
| Raqibul Hasan | 2 | 76 | 8.74 |
| Tarek M. Taha | 3 | 280 | 32.89 |
| Mark R. McLean | 4 | 1 | 0.37 |
| Doug Palmer | 5 | 1 | 0.37 |