Breaking News
Comments
Newest First | Oldest First | Threaded View
SOY
User Rank
Author
re: Memristor emulates neural learning
SOY   4/17/2010 9:52:37 AM
NO RATINGS
Johnson-san, Hi, thank you for your valuable articles. I think this is one of reconfigurable computing approaches (or simply FPGA based computings, and or Adaptive Computing from DARPA). And curbon nano-wire based PLD (nanoPLD) researched by Prof. Andre DeHon and the memoristor based computing researched by hp have common scense or face to common direction. Difference between them is probably how many states held by memory element (cross-point, nano-wire may be only one bit, but memoristor may hold multi-bit). Xbar network is the key that behaves both of the memory and interconnect. I request you to report not only the structure (or architecture) but also application and HOW TO PROGRAM at initial state or HOW TO CONFIGURE at initial state. Currently FPGA support JTAG based programming, but it is no scense. And I think this is solution for application-specific computing that means application is statically mapped to the device and does not change to other application (does not make context-switch). Of course, forcing the switching is possible, but it breaks data flow on device, this means a cost involving extra time and space if switching is taken.

R_Colin_Johnson
User Rank
Author
re: Memristor emulates neural learning
R_Colin_Johnson   4/16/2010 3:37:24 PM
NO RATINGS
Memristors are just a part of the solution. IBM, Hewlett Packard, HRL and their university partners are all looking at these other issues too. Look for a flurry of results over the next 6 to 18 months.

SOY
User Rank
Author
re: Memristor emulates neural learning
SOY   4/16/2010 11:53:31 AM
NO RATINGS
>Memristors do not provide a solution for this problem. As mentioned in the article, crossbar behaves as interconnection network, and its crosspoint is the synapse-like element.

Mapou
User Rank
Author
re: Memristor emulates neural learning
Mapou   4/16/2010 4:02:20 AM
NO RATINGS
Interesting. However, even though simulating a synapse or a neuron is nice but what is even more important is the ability to physically link those neurons to hundreds or thousands of other neurons in the network. Oftentimes, the neurons can be very distant. Memristors do not provide a solution for this problem. * Also, synaptic learning in the sensory cortex is not based on the concurrency of the spikes but on afferent signals arriving about 10 milliseconds before the post-synaptic action potential. See the work of Henry Markram for more on this.



Datasheets.com Parts Search

185 million searchable parts
(please enter a part number or hit search to begin)
Radio
LATEST ARCHIVED BROADCAST

What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.

Brought to you by:

Like Us on Facebook
Special Video Section
In this short video we show an LED light demo to ...
02:46
Wireless Power enables applications where it is difficult ...
07:41
LEDs are being used in current luxury model automotive ...
With design sizes expected to increase by 5X through 2020, ...
01:48
Linear Technology’s LT8330 and LT8331, two Low Quiescent ...
The quality and reliability of Mill-Max's two-piece ...
LED lighting is an important feature in today’s and future ...
05:27
The LT8602 has two high voltage buck regulators with an ...
05:18
Silego Technology’s highly versatile Mixed-signal GreenPAK ...
The quality and reliability of Mill-Max's two-piece ...
01:34
Why the multicopter? It has every thing in it. 58 of ...
Security is important in all parts of the IoT chain, ...
Infineon explains their philosophy and why the multicopter ...
The LTC4282 Hot SwapTM controller allows a board to be ...
This video highlights the Zynq® UltraScale+™ MPSoC, and sho...
Homeowners may soon be able to store the energy generated ...
The LTC®6363 is a low power, low noise, fully differential ...
See the Virtex® UltraScale+™ FPGA with 32.75G backplane ...
Vincent Ching, applications engineer at Avago Technologies, ...
The LT®6375 is a unity-gain difference amplifier which ...