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PD0RDD > NASA 11.09.98 18:32l 122 Lines 5781 Bytes #-10084 (0) @ WW
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From: PD0RDD@PI8WNO.#UTR.NLD.EU
To : NASA@WW
Onderwerp: JPL Neural Network Chip Paves the Way to a Cleaner America as Ford
Signs Licensing Agreement
Jim Cast
Headquarters, Washington, DC September 10, 1998
(Phone: 202/358-1779)
John Watson
Jet Propulsion Laboratory, Pasadena, CA
(Phone: 818/354-5011)
RELEASE: 98-161
JPL NEURAL NETWORK CHIP PAVES THE WAY TO A
CLEANER AMERICA AS FORD SIGNS LICENSING AGREEMENT
A new computer chip that mimics how the human mind works is
making its way from the space program to American industry and may
end up in millions of American cars in years to come.
NASA's Jet Propulsion Laboratory (JPL), Pasadena, CA, and the
Ford Motor Co. have signed a licensing agreement for use of an
advanced neural network technology to diagnose misfiring under the
hoods of Ford automobiles, among its many potential applications.
With the advent of this new chip, vehicles should show a reduction
in emission levels.
The smart fit between JPL's neural net hardware and Ford's
automotive engineering algorithm expertise will enhance the
industrial giant's ability to meet ever-stricter Clean Air Act
requirements as they apply to continuous onboard diagnostics and
control, officials said.
In addition, the chip is designed to improve fuel economy,
resulting in financial savings for car owners. Ford engineers do
not predict a price increase for installation of the chip because
JPL designed a computationally powerful neuroprocessor that could
be mass-produced in a highly cost-effective way. The technology
also improves customer satisfaction by virtually eliminating
distracting false alarms about misfiring that vehicle dashboards
can signal with current under-the-hood diagnostic technology.
JPL and Ford scientists say the chip represents the first
significant change in the way computing is done on vehicles since
computers were first introduced into automobiles in the 1970s.
"Neural networks are a new discipline, and diagnostics,
prognostics and control is a huge field. Ford's application is
but the tip of the iceberg of this chip's potential use in
American industry as a whole," said Tom Hamilton, program manager
at JPL's Dual-Use Technology Office, one of JPL's many technology
transfer arms. "JPL is proud to be able to make this
revolutionary technology available for U.S. business."
The new licensing agreement provides Ford with rights to
intellectual property of the chip for auto industry applications,
while JPL, which has applied for patents to the technology,
retains general rights. JPL is managed by the California
Institute of Technology, which serves as the party of record for
this license.
Neural systems were inspired by the architecture of nervous
systems of animals, which use neurons, a form of parallel
processing elements, to process large volumes of information
simultaneously. In vehicle applications, artificial neural
networks will "learn" both how to diagnose problems like engine
misfires and control the engine to optimize fuel economy and
emissions.
"What JPL has brought to the table is expertise in designing
and building what are known as neural network 'application-
specific integrated circuits'," said Dr. Raoul Tawel, who led the
development at JPL for the chip. "With Ford, we are implementing
highly complex neural network software code in dedicated hardware
logic. This brings about a tremendous boost in computational
ability compared to traditional software-based approaches,
enabling real-time onboard diagnostics for the first time."
For misfire diagnostics, it is necessary to observe and
diagnose every engine firing event, estimated at over one billion
in the life of each car.
In addition, the diagnostic error rate has to be extremely
small, less than one in a million, in order to avoid sending false
alarm signals to the driver. The new chip will accomplish that
task by "learning" diagnostic tasks during the vehicle development
process, bypassing the need to develop conventional software that,
in any event, can neither perform these tasks as well nor be
implemented in large production volumes with standard
microprocessors. The neural network chip, designed to carry out
parallel neuron computations efficiently, overcomes the
computational barriers that prevent this technology from being
exploited today.
A detailed, technical explanation of the technology written
by Tawel and Drs. Ken Marko and Lee Feldkamp of Ford's neural
network team, among several others, is available on the Web.
"Custom VLSI ASIC for Automotive Applications with Recurrent
Networks" can be accessed at
http://www.jpl.nasa.gov/releases/98/ijcnn98.pdf
For further information about JPL's technology transfer
programs, visit http://techtrans.jpl.nasa.gov/tu.html
-end-
.
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