We specialize in innovative systems and technologies
derived from light and utilizing emergent algorithms
The Heart of Future Optical Communication Systems
The key to a secure, fast and reliable system to transmit the world's signals
effectively, lies solely with optical communication technology. Technologies
to increase bandwidth and speed for all communications is at the core of
today's research.
The future of high bandwidth lies with technologies found in optical
communications systems. As trained electrical engineers, we are involved in
developing new technologies using innovative optical communication
techniques, which will enable and enhance the future of communications.
derived from light and utilizing emergent algorithms
The Heart of Future Optical Communication Systems
The key to a secure, fast and reliable system to transmit the world's signals
effectively, lies solely with optical communication technology. Technologies
to increase bandwidth and speed for all communications is at the core of
today's research.
The future of high bandwidth lies with technologies found in optical
communications systems. As trained electrical engineers, we are involved in
developing new technologies using innovative optical communication
techniques, which will enable and enhance the future of communications.
Our data streams are compressed and transmitted faster and more efficiently
Digital signals can be compressed and transmitted faster and more efficiently from place to place, or
enhanced to provide new information.
By changing signals from analog to digital we gain the advantage of higher speed transmission as well as
greater accuracy. We can also use DSP in other applications because it is programmable.
Digital signals can be compressed and transmitted faster and more efficiently from place to place, or
enhanced to provide new information.
By changing signals from analog to digital we gain the advantage of higher speed transmission as well as
greater accuracy. We can also use DSP in other applications because it is programmable.
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| Symmetric key algorithms are used to protect your information We use a form of communication where transmitters encode the message being sent into an optical signal to be transported to the receiver. The message is then returned to its original understandable form. Unique cipher codes are added to insure security of all information. |
Emergent Computation and Concepts in Algorithms
Innovations in optical communication and security technology can be developed using a new concept called
emergent computation.
Emergent computation or algorithms is a paradigm inspired by biological systems in which complex global behavior arises from the local interactions of large numbers of simple components.
Exploiting this paradigm for engineering complex systems offers significant advantages over conventional
centralized software and hardware systems since the algorithmic complexity is achieved through simple
components, each implementing simple rules, with well-defined interfaces and easily testable functionality.
The problems solved by such systems are solved in a massively parallel fashion and offering the possibility to
exploit redundancy and fault tolerance.
In a complex computing or communications system based on emergent computation, the output of a system
results from an autonomous decision made by each part, based on its own interpretation of the data or
information.
For instance, like a bee communicating to others an intelligent decision is made by the swarm, based on
information from its parts, while no central information processor is present or needed.
Theorists in many fields are excited by this new concept. In computer engineering, it suggests that the
computer not only can play the role of an autonomous agent in decision-making situations categorized as
routine but even in some novel situations.
Of course, what are these situations? Speculatively, we could note the use of these learning models in space
exploration and social spaces characterized by abundant data. Although the former is understandable, given
the autonomous nature of probes traveling to the far reaches of the solar system, the latter is somewhat more
challenging to envision.
One possibility is in the realm of highly complex systems that not only demonstrate emergent properties such as
adaptation but also are characterized by our inability to effectively reduce their form, processes, and outcomes
to analytically ordered models.
Emergent computation is potentially relevant to several areas, including adaptive systems (complex social
regimes under policy interventions), parallel processing, and cognitive and biological modeling, and other
communication and software systems.
Scientists are beginning to see that the concept of emergent computation occurs in nature and this can be
used to study natural patterns in phenomena and develop solutions to specific problems in fields of research.
We used this concept in developing our optical communication and security innovations.
Many biological systems appear to carry out this type of distributed computation-- for instance, ant colonies,
nervous systems, and immune systems. One favorite example among biologists is slime molds, which exist for
most of their lives as single-celled, amoeba-like creatures.
When their food supply runs dry, they somehow figure out, through local signals between cells, how to swarm
together into a slug-like, multi-cellular organism that produces the spores that give rise to the next generation.
Unlike traditional computation, in which a central processing unit carries out programs, distributed emergent
computation lacks a central controller. Instead, large numbers of simple units interact with each other to
achieve complex, large-scale computations.
Plants may perform what scientists call distributed emergent computation. Although the plants don't add,
subtract, multiply, or divide, they do seem to compute solutions to problems of how to coordinate the actions of
their cells effectively.
Researchers believe plants may use computation to figure out how wide to open pores in their leaves. The leaf
pores, also called stomata, open to allow in carbon dioxide, which plants need for photosynthesis. However,
open pores also let out water and so may dehydrate the plant. To balance these competing factors as
environmental factors change, plants constantly adjust how many and how widely their pores are open.
The way that plants achieve this balance has been a mystery. There's no brain to coordinate the tens of
thousands of pores, and individual pores seem to have no way of knowing what distant pores are doing.
At first, biologists thought that each pore simply decided independently what action to take. About 10 years
ago, however, researchers noticed that large patches of pores frequently open and close in concert. More
recently, Keith Mott, a biologist at Utah State University in Logan, discovered that over minutes, these patches
of synchronization move about the leaf; often displaying complex dynamics.
He described these observations to physicist David Peak, a colleague at Utah State. They reminded Peak of
patterns that turn up in cellular automata, a kind of distributed emergent computer.
"It occurred to us that the patterns could be symptomatic of a distributed emergent Computation," Mott says.
Mott and Peak next investigated whether there was more to the seeming similarity between the behavior of leaf
pores and of cellular automata. A cellular automaton consists of a collection of units called cells, each of which
can be in one of several states. Over time, the cells change their states according to rules that depend on their
current states and those of their neighbors.
The best-known cellular automaton is the Game of Life, invented in 1970 by British mathematician John
Conway, now at Princeton University. The game consists of a grid of cells, each of which is considered to be
either dead or alive. At each time step, some cells switch state according to simple rules.
An example of this is when a live cell with at least four living neighbors dies of overpopulation. Even though
each cell is influenced only--by nearby cells, complicated global patterns can emerge. Cellular automata
may underlie nearly all phenomena, from the physics of elementary particles to life and intelligence.
Although, most scientists don't subscribe to such a sweeping concept, they are using principles of emergent
computation to process images, model earthquakes, traffic patterns, ecological patterns and migration of
animals, and neural circuits and tumor growth. For additional information research articles on emergent
computation and algorithm development see Emergent Computation
Innovations in optical communication and security technology can be developed using a new concept called
emergent computation.
Emergent computation or algorithms is a paradigm inspired by biological systems in which complex global behavior arises from the local interactions of large numbers of simple components.
Exploiting this paradigm for engineering complex systems offers significant advantages over conventional
centralized software and hardware systems since the algorithmic complexity is achieved through simple
components, each implementing simple rules, with well-defined interfaces and easily testable functionality.
The problems solved by such systems are solved in a massively parallel fashion and offering the possibility to
exploit redundancy and fault tolerance.
In a complex computing or communications system based on emergent computation, the output of a system
results from an autonomous decision made by each part, based on its own interpretation of the data or
information.
For instance, like a bee communicating to others an intelligent decision is made by the swarm, based on
information from its parts, while no central information processor is present or needed.
Theorists in many fields are excited by this new concept. In computer engineering, it suggests that the
computer not only can play the role of an autonomous agent in decision-making situations categorized as
routine but even in some novel situations.
Of course, what are these situations? Speculatively, we could note the use of these learning models in space
exploration and social spaces characterized by abundant data. Although the former is understandable, given
the autonomous nature of probes traveling to the far reaches of the solar system, the latter is somewhat more
challenging to envision.
One possibility is in the realm of highly complex systems that not only demonstrate emergent properties such as
adaptation but also are characterized by our inability to effectively reduce their form, processes, and outcomes
to analytically ordered models.
Emergent computation is potentially relevant to several areas, including adaptive systems (complex social
regimes under policy interventions), parallel processing, and cognitive and biological modeling, and other
communication and software systems.
Scientists are beginning to see that the concept of emergent computation occurs in nature and this can be
used to study natural patterns in phenomena and develop solutions to specific problems in fields of research.
We used this concept in developing our optical communication and security innovations.
Many biological systems appear to carry out this type of distributed computation-- for instance, ant colonies,
nervous systems, and immune systems. One favorite example among biologists is slime molds, which exist for
most of their lives as single-celled, amoeba-like creatures.
When their food supply runs dry, they somehow figure out, through local signals between cells, how to swarm
together into a slug-like, multi-cellular organism that produces the spores that give rise to the next generation.
Unlike traditional computation, in which a central processing unit carries out programs, distributed emergent
computation lacks a central controller. Instead, large numbers of simple units interact with each other to
achieve complex, large-scale computations.
Plants may perform what scientists call distributed emergent computation. Although the plants don't add,
subtract, multiply, or divide, they do seem to compute solutions to problems of how to coordinate the actions of
their cells effectively.
Researchers believe plants may use computation to figure out how wide to open pores in their leaves. The leaf
pores, also called stomata, open to allow in carbon dioxide, which plants need for photosynthesis. However,
open pores also let out water and so may dehydrate the plant. To balance these competing factors as
environmental factors change, plants constantly adjust how many and how widely their pores are open.
The way that plants achieve this balance has been a mystery. There's no brain to coordinate the tens of
thousands of pores, and individual pores seem to have no way of knowing what distant pores are doing.
At first, biologists thought that each pore simply decided independently what action to take. About 10 years
ago, however, researchers noticed that large patches of pores frequently open and close in concert. More
recently, Keith Mott, a biologist at Utah State University in Logan, discovered that over minutes, these patches
of synchronization move about the leaf; often displaying complex dynamics.
He described these observations to physicist David Peak, a colleague at Utah State. They reminded Peak of
patterns that turn up in cellular automata, a kind of distributed emergent computer.
"It occurred to us that the patterns could be symptomatic of a distributed emergent Computation," Mott says.
Mott and Peak next investigated whether there was more to the seeming similarity between the behavior of leaf
pores and of cellular automata. A cellular automaton consists of a collection of units called cells, each of which
can be in one of several states. Over time, the cells change their states according to rules that depend on their
current states and those of their neighbors.
The best-known cellular automaton is the Game of Life, invented in 1970 by British mathematician John
Conway, now at Princeton University. The game consists of a grid of cells, each of which is considered to be
either dead or alive. At each time step, some cells switch state according to simple rules.
An example of this is when a live cell with at least four living neighbors dies of overpopulation. Even though
each cell is influenced only--by nearby cells, complicated global patterns can emerge. Cellular automata
may underlie nearly all phenomena, from the physics of elementary particles to life and intelligence.
Although, most scientists don't subscribe to such a sweeping concept, they are using principles of emergent
computation to process images, model earthquakes, traffic patterns, ecological patterns and migration of
animals, and neural circuits and tumor growth. For additional information research articles on emergent
computation and algorithm development see Emergent Computation
| Products developed from experiments in optical communications Innovative products are derived from experiments in integrated optical wave-guides (monomode and multimode) and related optical communications and includes optical technologies used in security. If you like this site, you will also enjoy our great Sister sites: Native jewelry and kachina dolls Mini horses Aquarium fish, clown fish and aquarium coral Native art, medicine wheels, native pottery Sacagawea: Her life, death and birth tribe |