Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

ASU advance could provide insight into human’s ability to recognize patterns

11.05.2004


Computers, for all of their computational muscle, do not hold a candle to humans in the ability to recognize patterns or images. This basic quandary in computational theory – why can computers crunch numbers but cannot efficiently process images – has stumped scientists for many years.



Now, researchers at Arizona State University have come up with a model that could help unlock some of the secrets of how humans process patterns and possibly lead to smarter robots. The advance concerns oscillatory associative memory networks, basically the ability to see a pattern, store it and then retrieve that pattern when needed. A good example is how humans can recognize faces.

"It is still a really big mystery as to how human beings can remember so many faces, but that it is extremely difficult for a computer to do," said Ying-Cheng Lai, an ASU professor of mathematics and a professor of electrical engineering in the Ira A. Fulton School of Engineering.


Lai, along with former post-doctoral fellow Takashi Nishikawa (now at Southern Methodist University), and former ASU professor Frank Hoppenstaedt (now at New York University), published their research, "Capacity of Oscillatory Associative Memory Networks with Error-Free Retrieval," in a recent issue of American Physical Society’s Physical Review Letters.

Although what the team developed is a mathematical and computational model for oscillatory networks that can be used associated memory devices, implementation of the model is possible by using electronic circuits as phase-locked loops.

"Computers can do very fast computation that humans cannot do, but humans can recognize patterns so much better than computers," Lai said. "The question is why. What is the fundamental mechanism that a biological system like us can make use of and try to memorize patterns."

A key to pattern recognition is the use of oscillatory associative memory networks. Lai said the human brain and its use of neurons have a great advantage over computer memory in that they employ oscillatory memory systems, systems where the individual components can oscillate or freely change between states. In contrast, digital computer memories operate on a binary number system (1 or 0).

An important advance was made in this area in the 1980s by John Hopfield, a Caltech researcher at the time, who developed the "Hopfield network" to help understand how biological memory works. But the main drawback of the Hopfield network is that while it represents how biological memory works, it employs discrete state memory units while most biological units are oscillatory.

"Our work is the first demonstration of the possibility for oscillatory networks to have the same memory capacity as for the discrete-state Hopfield network," Lai said. "When the Hopfield network was invented, it was considered a revolutionary step in understanding how biological memory works.

"A difficulty with the Hopfield network is that it consists of units (or artificial neurons) with two discrete states," he added. "It is therefore desirable to study oscillatory networks but this has been a struggle, as all previous work shows that the capacities of these networks are very low compared with that of the Hopfield network. In a sense, our work helps solve this difficulty."

Lai said that the most immediate application for this research is in artificial intelligence, where researchers try to get computers to reason as a human would. He adds that this advance could possibly allow the development of artificial memory devices that would use oscillators, which are robust and secure.

This could mean robots, or other electro-mechanical devices controlled by an electronic "brain" that could recognize patterns and do some form of reasoning on the fly -- basically respond to a much wider range of unanticipated situations -- to perform its task. This would be a big step towards smarter robots.

But the real payoff in Lai’s research could be what it may provide in terms of basic research into the human brain itself. Developing a good model of the human brain, one that could more closely replicate the actual function of the brain as it reasons, might help understand more of its operational basis and how it developed into the organ it is today.

"Biological systems, such as cells and neurons, are oscillators," Lai explained. "Demonstrating that oscillatory networks can have memories with high capacity is one more step toward understanding biological memory.

"Although the classical Hopfield network provides a plausible mechanism for memory, it has the drawback that it is too idealized as compared with real, oscillatory biological networks," he added. "We hope our work will stimulate further studies of the origin of memory based systems on a more realistic oscillatory network."


Source: Ying-Cheng Lai, (480) 965-6668

Skip Derra | EurekAlert!
Further information:
http://www.asu.edu/asunews/

More articles from Interdisciplinary Research:

nachricht Easier Diagnosis of Esophageal Cancer
06.03.2017 | Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt

nachricht Sandia uses confined nanoparticles to improve hydrogen storage materials performance
27.02.2017 | DOE/Sandia National Laboratories

All articles from Interdisciplinary Research >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: A Challenging European Research Project to Develop New Tiny Microscopes

The Institute of Semiconductor Technology and the Institute of Physical and Theoretical Chemistry, both members of the Laboratory for Emerging Nanometrology (LENA), at Technische Universität Braunschweig are partners in a new European research project entitled ChipScope, which aims to develop a completely new and extremely small optical microscope capable of observing the interior of living cells in real time. A consortium of 7 partners from 5 countries will tackle this issue with very ambitious objectives during a four-year research program.

To demonstrate the usefulness of this new scientific tool, at the end of the project the developed chip-sized microscope will be used to observe in real-time...

Im Focus: Giant Magnetic Fields in the Universe

Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.

The results will be published on March 22 in the journal „Astronomy & Astrophysics“.

Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...

Im Focus: Tracing down linear ubiquitination

Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.

Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...

Im Focus: Perovskite edges can be tuned for optoelectronic performance

Layered 2D material improves efficiency for solar cells and LEDs

In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...

Im Focus: Polymer-coated silicon nanosheets as alternative to graphene: A perfect team for nanoelectronics

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

International Land Use Symposium ILUS 2017: Call for Abstracts and Registration open

20.03.2017 | Event News

CONNECT 2017: International congress on connective tissue

14.03.2017 | Event News

ICTM Conference: Turbine Construction between Big Data and Additive Manufacturing

07.03.2017 | Event News

 
Latest News

Transport of molecular motors into cilia

28.03.2017 | Life Sciences

A novel hybrid UAV that may change the way people operate drones

28.03.2017 | Information Technology

NASA spacecraft investigate clues in radiation belts

28.03.2017 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>