1. A nonlinear fiber having a core and a cladding and having a third-order nonlinear coefficient of at least 30 W\u22121km\u22121 to a light having a wavelength of 1,550 nm, which contains Er or Tm in the cladding at a portion within 3 \u03bcm from the interface with the core.
2. The nonlinear fiber according to claim 1, wherein the core is made of glass consisting essentially of 35 to 50 mol % of Bi2O3, from 30 to 40 mol % of B2O3+SiO2, from 15 to 25 mol % of Al2O3+Ga2O3 and from 0 to 1 mol % of CeO2, and the cladding at a portion within 3 \u03bcm from the interface with the core is made of a base glass consisting essentially of 35 to 50 mol % of Bi2O3, from 30 to 40 mol % of B2O3+SiO2, from 15 to 25 mol % of Al2O3+Ga2O3 and from 0 to 1 mol % of CeO2 and containing Er or Tm.
3. The nonlinear fiber according to claim 1, wherein the clad at a portion within 3 \u03bcm from the interface with the core contains Er in a content of at least 40 ppm as represented by mass percentage.
4. A wavelength conversion method of making a signal light having a wavelength \u03bbS and an intensity IS and a pump light having a wavelength \u03bbP which is shorter than 2\u03bbS and an intensity higher than IS enter a nonlinear fiber having a core and a cladding, and generating a converted light having a wavelength \u03bbC of \u03bbS\u03bbP(2\u03bbS\u2212\u03bbP) and an intensity ICby four wave mixing, wherein Er or Tm is present in the cladding at a portion with a diameter in the nonlinear fiber of at most the mode field diameter, and the converted light is generated by four wave mixing while Er or Tm is excited by an excitation light.
5. The wavelength conversion method according to claim 4, wherein the difference between the core diameter and the mode field diameter of the nonlinear fiber is at most 3 \u03bcm, and the nonlinear fiber is the nonlinear fiber as defined in claim 1.
6. The wavelength conversion method according to claim 4, wherein \u03bbS is from 1,530 to 1,620 nm, Er is present in the cladding at a portion with a diameter in the nonlinear fiber of at most the mode field diameter, and the wavelength of the excitation light is from 1,475 to 1,485 nm.
7. A wavelength conversion device of making a signal light having a wavelength \u03bbS and an intensity IS and a pump light having a wavelength \u03bbP which is shorter than 2\u03bbS and an intensity higher than IS enter a nonlinear fiber, and generating a converted light having a wavelength \u03bbC of \u03bbS\u03bbP(2\u03bbS\u2212\u03bbP) by four wave mixing, wherein the nonlinear fiber is the nonlinear fiber as defined in claim 1, and the device has an input terminal for an excitation light to excite Er or Tm present in the cladding of the nonlinear fiber at a portion within 3 \u03bcm from the interface with the core.
8. A wavelength conversion device of making a signal light having a wavelength \u03bbS and an intensity IS and a pump light having a wavelength \u03bbP which is shorter than 2\u03bbS and an intensity higher than IS enter a nonlinear fiber, and generating a converted light having a wavelength \u03bbC of \u03bbS\u03bbP(2\u03bbS\u2212\u03bbP) by four wave mixing, wherein the intensity of the converted light can be made to be at least (IS\xd710\u22124) even when the pump light intensity is at most 20 mW, and the length of the nonlinear fiber is at most 10 m.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A Runtime forward-chaining reasoning method of data tuples andor rules to be inserted andor deleted, comprising: keeping record of inference counters for each data tuple in order to provide delete operation that doesn’t require re-calculation of tuples inferred earlier.
2. The method of claim 1 wherein the method comprises re-running the method every time the set of explicit data tuples or rule set is changed.
3. The method of claim 1 wherein the method comprises at least one of the following: insertion of a tuple, deletion of a tuple, insertion of a rule, deletion of a rule,
4. The method of claim 1 wherein the said changes of said tuples andor rules are arranged to be inputted so that they avoid re-inference of an existing implicit tuple.
5. The method of claim 4 wherein the method comprises inferring all implicit tuples when an ensemble of all explicit data tuples andor an ensemble of all explicit rules havehas been inserted into the system.
6. The method of claim 1, wherein the method comprises making accessible at least one of the tuples of all explicit data tuples by using the terms of tuple pattern search.
7. The method of claim 6 wherein a sub-ensemble of all implicit or explicit data tuples is loaded into the working memory used by the system.
8. The method of claim 1, wherein method comprises at least one of the following:
evaluating sequentially at least one rule of the rules in the system,
inserting resulting implicit tuples,’
deleting resulting implicit tuples and
updating inference counters.
9. The method of claim 8, wherein the method comprises variable substitution for tuple pattern searches to search relevant tuples for any of the operations.
10. The method of claim 1, wherein the method comprises selection of the appropriate existing rules to be evaluated.
11. The method of claim 10, wherein the method comprises identifying a number of loops andor repeating the evaluation until the system will not change anymore.
12. The method of claim 8, wherein the method comprises stopping recursion of a tuple as a response to an initiative of observation of having the same explicit tuple and rule combination being processed already.
13. The method according to claim 1, wherein the method comprises distributing at least one method step into another processing node than the executing node before said distributing.
14. The method of claim 13, wherein the method comprises providing said another node with individual working memory, shared access to a rule set andor right to execute a tuple pattern search against shared tuple data.
15. A system configured to execute the method according to claim 1.
16. A system element of the system of claim 15, comprising executing means to perform a method step of a previous method claim.
17. A codec or a decoder comprising means of said system element of claim 16.
18. A codec or a decoder of claim 17 comprising a data base module to access to a data base of rules, tuples andor configuration data.
19. An inference engine, configured to execute a method according to claim 1.
20. An expert system comprising a system element of claim 16, wherein the system comprises at least one of the following:
User interface,
A knowledge-base,
A knowledge acquisition module and
An explanatory interface.
21. A software product comprising software means that are configured to load a computer code into a memory of a computer to be executed in a processor connected to said memory a computer code arranged to execute an embodied method.