Yuriy Pershin of the University of South Carolina, Columbia, and Massimiliano Di Ventra of the University of California, San Diego, two researchers that have done some work in the past on memristors, have published an article that explains a memristive hardware-based method to automatically solve mazes. Read the rest of this entry »
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The memristor maze solver
| March 9, 2011 -
The Neuromorphics Lab on the cover page of IEEE Computer
| February 10, 2011
For the memristors/neuromorphic computing aficionados, a new article featured on the cover page of the February edition of IEEE Computer describing the joint work done by Hewlett-Packard and the Neuromorphics Lab at Boston University summarizing the challenges and the accomplishments of the past year. And what a year! The abstract says it all: "In a synchronous digital platform for building large cognitive models, memristive nanodevices form dense, resistive memories that can be placed close to conventional processing circuitry. Through adaptive transformations, the devices can interact with the world in real time." Read the rest of this entry »Comments: Leave a comment -
Memristors – a revolutionary research field
| December 19, 2010
In 1971, Prof. Leon Chua from UC Berkeley published an article about the memristor, a fourth passive element in electronics (in addition to resistor, capacitor and inductor). Since Chua's article, memristors have become an exciting device that potentially can revolutionize the electronic industry. Chua predicted, only because of symmetry reasons, that there is a missing passive element, whose main characteristic is a relationship between flux (the total voltage being applied on it) and electric charge (the total current that had flown through it). Such a device actually acts as a resistor, but unlike the conventional resistor, its resistance is not constant, nor depends upon the temporary voltage being applied to it (as is the case for non-linear resistors). Read the rest of this entry »
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Modeling the HP memristor with SPICE
| July 23, 2010
After writing several memristor models with SPICE last week, I decided to post a short tutorial here on the subject. I'll concentrate on modeling the memristor introduced in the Nature Nanoletters' article Memristive Switching mechanism for metal/oxide/metal nanodevices by Yang et al., published in July 2008. More specifically the model is an enhanced version of the one derived in the article CNN Using Memristors for Neighborhood Connections (IEEE CNNA 2010) by me and Mika Laiho. Read the rest of this entry » -
Second Memristor and Memristive Systems Symposium
| March 7, 2010
The 2nd Memristor and Memristive Systems Symposium took place on Tuesday, February 2, 2010 at Sutardja Dai Hall, UC Berkeley. The 2010 symposium covered memristor technology updates, new device technologies (materials and fabrication), device models for CAD, novel circuits using memristors, and systems architecture harnessing memristor and memristive device properties. Read the rest of this entry »Comments: 2 CommentsCategories: Computing -
A 6-Minute Memristor Guide
| October 25, 2009
Stanley Williams, whose team discovered the fourth fundamental circuit element, the memristor, gives a brief talk about how the device works. Read the rest of this entry » -
A brief history of the memristor: from Leon Chua, to HP, to Boston University
| July 8, 2009
Justin Mullins is the author of a nice post on the Memristor, appeard on 7/8/2009 on New Scientist. It does a nice job in describing the story of the memristor, from his theoretical discovery in 1971 by Leon Chua at the University of California, Berkeley, to his utilization by Stan Williams and Greg Snider at the HP Labs in Palo Alto, to the implementation of neural models, which involves the department that hosts the Neurdons!... Read the rest of this entry » -
“Hello World” on Memristive Nanodevices
| February 3, 2009SyNAPSE is not a project DARPA undertook lightly. Many attempts at large-scale neuromorphic engineering have been made in the past. None met their goals. As such, SyNAPSE owes its existence to a number of recent game-changing developments. From HP Labs, the discovery of the memristor was one such keystone innovation. It took Greg Snider's 2007 work in Nanotechnology, however, to establish memristors as a viable platform for the implementation of self-organizing recurrent neural networks.
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The Brainputer
| February 2, 2009After running through the Businessweek article posted by Max, I am equally excited and nervous. Anyone has to be excited over the prospect of a new computing paradigm, though honestly I'm not sure what that looks like yet. These sorts of articles claim that computers will look more like brains, which is all well and good, because brains tend to do dominate the "competition", i.e. computers, at messy things like object recognition and speech recognition. Conversely (and obviously), computers tend to dominate tasks amenable to decomposition into easily formalizable sequential steps, e.g. chess or even eye surgery. So, maybe we know what Deep Blue looks like, but what on Earth would a computer expert in messy things, a messy computer if you'll excuse the phrase, even look like? We all agree that computers stink at these messy things, and if they didn't stink at them it would be a huge boon to, well, humankind. So let's make the computers more like brains so they can do what brains do so well! But how do we make computers, both in terms of hardware and software, more like brains?
