1. A computer system for generating standardized product data, the computer system comprising:
a database operable to maintain data for a plurality of known products, each known product associated with a respective standardized product code; and
a processing facility coupled to the database, the processing facility operable to receive raw data for an unidentified product from a plurality of diverse data sources each of which has its own separate identifier for the unidentified product, to compare the raw data for the unidentified product against the data for the plurality of known products, and if there is a match between the raw data for the unidentified product and the data for one of the plurality of known products, to assign the respective standardized product code of the matching known product to the unidentified products,
wherein the raw data comprises a raw description for the unidentified product the data maintained in the database comprises a separate stored description for each of the plurality of known products, and the processing facility is operable to compare the raw description for the unidentified product against the stored descriptions for each of the plurality of known products.
2. The computer system of claim 1 wherein the processing facility is operable to parse the raw data into a number of separate fields values for the unidentified product.
3. The computer system of claim 1 wherein the processing facility is operable to generate at least one guess as to a known product which is a possible match for the unidentified product.
4. The computer system of claim 3 wherein the processing facility is operable to generate a confidence measure for the at least one guess.
5. The computer system of claim 1 further comprising an interface coupled to the processing facility, the interface operable to present the assigned standardized product code to an analyst for auditing.
6. The computer system of claim 1 wherein the processing facility is further operable to update the database with the raw data for the unidentified product, in order to improve future data comparisons.
7. The computer system of claim 1 wherein, if there is no match between the raw data for the unidentified product and the data for any of the plurality of known products, the processing facility is further operable to create a new standardized product code and assign the new standardized product code to the unidentified product.
8. A method performed on a computer system for generating standardized product data, the method comprising:
maintaining data for a plurality of known products, each known product associated with a respective standardized product code;
receiving raw data for an unidentified product from a plurality of diverse data sources, each data source having its own separate identifier for the unidentified product;
comparing the raw data for the unidentified product against the data for the plurality of known products; and
if there is a match between the raw data for the unidentified product and the data for one of the plurality of known products, assigning the respective standardized product code of the matching known product to the unidentified product
wherein the raw data comprises a raw description for the unidentified product and the maintained data comprises a separate stored description for each of the plurality of known products, and wherein comparing comprises comparing the raw description for the unidentified product against the stored descriptions for each of the plurality of known products.
9. The method of claim 8 comprising presenting the assigned standardized product code to an analyst for auditing.
10. The method of claim 8 comprising parsing the raw data into a number of separate fields values for the unidentified product.
11. The method of claim 8 comprising generating at least one guess as to a known product which is a possible match for the unidentified product.
12. The method of claim 11 comprising presenting the at least one guess to an analyst for assigning a standardized product code to the unidentified product.
13. The method of claim 11 wherein the raw data comprises a number of field values for the unidentified product and the maintained data comprises separate field values for each of the plurality of known products, and wherein generating comprises performing a pattern comparison of the field values for the unidentified product against the field values for each known product.
14. The method of claim 8 further comprising the step of updating the database with the raw data for the unidentified product, in order to improve future data comparisons.
15. The method of claim 8 further comprising the steps of:
if there is no match between the raw data for the unidentified product and the data for any of the plurality of known products, creating a new standardized product code; and
assigning the new standardized product code to the unidentified product.
16. A computer system for generating standardized product data, the computer system comprising:
a database operable to maintain data for a plurality of known products, each known product associated with a respective standardized product code, the data maintained in the database comprising a separate stored description and set of field values for each of the plurality of known products;
a processing facility coupled to the database and operable to:
receive raw data for an unidentified product from a plurality of diverse data sources each of which has its own separate identifier for the unidentified product, the raw data comprising a raw description and set of field values for the unidentified product,
compare the raw description for the unidentified product against the stored descriptions for each of the plurality of known products,
if the raw description for the unidentified product does not match any of the stored descriptions for the plurality of known products, compare a predetermined combination of the field values for the unidentified product against corresponding field values for each of the plurality of known products, and
if the raw description for the unidentified product matches a stored description for one of the plurality of known products, or if all of the field values for the unidentified product match the corresponding field values for one of the plurality of known products for the predetermined combination, assign the respective standardized product code of the matching known product to the unidentified product.
17. The computer system of claim 16 wherein the processing facility is operable to parse the raw data into the fields values for the unidentified product.
18. The computer system of claim 16 comprising an interface coupled to the processing facility, the interface operable to present the assigned standardized product code to an analyst for auditing.
19. The computer system of claim 16 wherein the processing facility is operable to generate at least one guess as to a known product which is a possible match for the unidentified product.
20. The computer system of claim 19 wherein the processing facility is operable to generate a confidence measure for the at least one guess.
21. The computer system of claim 20 comprising an interface coupled to the processing facility, the interface operable to present the at least one guess and confidence measure to an analyst for assignment of a standardized product code.
22. A method performed on a computer system for generating standardized product data, the method comprising:
receiving raw data for an unidentified product from a plurality of diverse data sources each of which has its own separate identifier for the unidentified product, the raw data comprising a raw description and set of field values for the unidentified product;
comparing the raw description for the unidentified product against the stored descriptions for each of the plurality of known products;
if the raw description for the unidentified product does not match any stored description, comparing a predetermined combination of the field values for the unidentified product against corresponding field values for each of the plurality of known products; and
if the raw description for the unidentified product matches a stored description for one of the plurality of known products, or if all of the field values for the unidentified product match the corresponding field values for one of the plurality of known products for the predetermined combination, assigning the respective standardized product code of the matching known product to the unidentified product.
23. A computer system for generating standardized product data, the computer system comprising:
a database operable to maintain data for a plurality of known products, each known product associated with a respective standardized product code; and
a processing facility coupled to the database, the processing facility operable to receive raw data for an unidentified product from a plurality of diverse data sources each of which has its own separate identifier for the unidentified product, to compare the raw data for the unidentified product against the data for the plurality of known products, and if there is a match between the raw data for the unidentified product and the data for one of the plurality of known products, to assign the respective standardized product code of the matching known product to the unidentified product,
wherein the raw data comprises a number of field values for the unidentified product, the data maintained in the database comprises separate field values for each of the plurality of known products, and the processing facility is to compare a predetermined combination of the field values for the unidentified product against corresponding field values for each of the plurality of known products.
24. The computer system of claim 23 wherein the processing facility is operable to parse the raw data into a number of separate fields values for the unidentified product.
25. The computer system of claim 23 wherein the processing facility is operable to generate at least one guess as to a known product which is a possible match for the unidentified product.
26. The computer system of claim 25 wherein the processing facility is operable to generate a confidence measure for the at least one guess.
27. The computer system of claim 23 further comprising an interface coupled to the processing facility, the interface operable to present the assigned standardized product code to an analyst for auditing.
28. The computer system of claim 23 wherein the processing facility is further operable to update the database with the raw data for the unidentified product, in order to improve future data comparisons.
29. The computer system of claim 23 wherein, if there is no match between the raw data for the unidentified product and the data for any of the plurality of known products, the processing facility is further operable to create a new standardized product code and assign the new standardized product code to the unidentified product.
30. A method performed on a computer system for generating standardized product data, the method comprising:
maintaining data for a plurality of known products, each known product associated with a respective standardized product code;
receiving raw data for an unidentified product from a plurality of diverse data sources, each data source having its own separate identifier for the unidentified product;
comparing the raw data for the unidentified product against the data for the plurality of known products; and
if there is a match between the raw data for the unidentified product and the data for one of the plurality of known products, assigning the respective standardized product code of the matching known product to the unidentified product,
wherein the raw data comprises a number of field values for the unidentified product and the maintained data comprises separate field values for each of the plurality of known products, and wherein comparing comprises comparing a predetermined combination of the field values for the unidentified product against corresponding field values for each of the plurality of known products.
31. The method of claim 30 comprising presenting the assigned standardized product code to an analyst for auditing.
32. The method of claim 30 comprising parsing the raw data into a number of separate fields values for the unidentified product.
33. The method of claim 30 comprising generating at least one guess as to a known product which is a possible match for the unidentified product.
34. The method of claim 33 comprising presenting the at least one guess to an analyst for assigning a standardized product code to the unidentified product.
35. The method of claim 33 wherein generating comprises performing a pattern comparison of the field values for the unidentified product against the field values for each known product.
36. The method of claim 30 further comprising the step of updating the database with the raw data for the unidentified product, in order to improve future data comparisons.
37. The method of claim 30 further comprising the steps of:
if there is no match between the raw data for the unidentified product and the data for any of the plurality of known products, creating a new standardized product code; and
assigning the new standardized product code to the unidentified product.
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 method of compensating for a defect of an optical disc, comprising:
detecting a disc defect zone according to an RF sum signal level read from the optical disc;
inverting a phase of a tracking error signal generated during a first specified time from the start of the defect zone; and
holding a tracking servo control by adding components of the inverted tracking error signal to a tracking drive signal for a second specified time,
wherein the inverting includes:
sampling the tracking error signal generated during the predetermined time from the start of the defect zone;
inverting most significant bits of the sampled values; and
integrating the sampled values including the inverted most significant bits.
2. The method of claim 1, wherein the inverting includes inverting a phase of the tracking error signal, whose high-frequency component is compensated for, during a specified time starting from a point of time when a defect flag is changed to a logic high state.
3. An optical recordingreproducing apparatus comprising:
an optical pickup which converts optically detected information recorded on a disc into an electrical RF signal;
an RF amplifier which generates a focus error signal and a tracking error signal by amplifying the RF signal output from the optical pickup; and
a servo signal processing unit which outputs a tracking drive signal by compensating for a gain and phase of the tracking error signal generated by the RF amplifier, inverting the phase of the tracking error signal during a specified time from the start of a defect zone, and adding the phase-inverted tracking error signal to the tracking drive signal, the inverting including sampling the tracking error signal generated during the predetermined time from the start of the defect zone, inverting most significant bits of the sampled values, and integrating the sampled values including the inverted most significant bits.
4. The apparatus of claim 3, wherein the servo signal processing unit includes:
a high-frequency component compensator which compensates for a phase and gain of a high-frequency component of the tracking error signal;
a low-frequency component compensator which compensates for a phase and gain of a low-frequency component of the tracking error signal;
a defect compensator which inverts the phase of the tracking error signal output from the high-frequency component compensator during the specified time from the start of the defect zone;
a selector which selectively outputs the signal output from the high-frequency component compensator or the signal output from the defect compensator according to a defect flag signal generated when a defect is detected; and
an adder which adds the low-frequency tracking error signal compensated by the low-frequency component compensator and the high-frequency tracking error signal selected by the selector and outputs the result as the tracking drive signal.
5. The apparatus of claim 4, wherein the defect compensator includes:
a bit inverter which inverts most significant bits of the sampled values output from the high-frequency component compensator;
a register unit which sequentially stores sampled values including the inverted most significant bits output from the bit inverter;
an integrator which integrates the sampled values stored in the register unit when the defect flag is in a logic high state;
a gain regulator which regulates a gain of the signal integrated by the integrator.
6. The apparatus of claim 4, wherein the tracking error signal is digital and the apparatus further comprises an analog to digital converter which converts an analog tracking error signal into the digital tracking error signal.
7. The apparatus of claim 6, further comprising an anti-aliasing filter which anti-aliases the digital tracking error signal.
8. The apparatus of claim 7, further comprising:
a hold filter which extracts a DC component from the anti-aliased tracking error signal;
a register which stores the DC component; and
a switching unit which, according to a defect flag signal, selectively outputs the tracking error signal detected from the disc or a DC component stored in the register.
9. The apparatus of claim 4, further comprising a digital to analog converter which converts the tracking drive signal output by the adder into an analog tracking drive signal.
10. The apparatus of claim 3, wherein the optical pickup includes a tracking servo which is driven by a tracking actuator and a focusing servo which is driven by a focusing actuator.
11. The apparatus of claim 10, further comprising a driving unit which drives the focusing actuator and the tracking actuator using the tracking drive signal output from the servo signal processing unit.
12. The apparatus of claim 10, further comprising a drive unit which drives a disc motor which rotates the disc.
13. The apparatus of claim 3, wherein the RF amplifier includes a built-in focus error detecting circuit and a built-in tracking error detecting circuit which respectively generate the focus error signal and the tracking error signal.
14. A reproducing apparatus comprising:
an optical pickup which converts optically detected information recorded on a disc into an electrical RF signal;
an RF amplifier which generates a focus error signal and a tracking error signal by amplifying the RF signal output from the optical pickup; and
a servo signal processing unit which outputs a tracking drive signal by compensating for a gain and phase of the tracking error signal generated by the RF amplifier, inverting the phase of the tracking error signal during a specified time from the start of a defect zone, and adding the phase-inverted tracking error signal to the tracking drive signal, the inverting including sampling the tracking error signal generated during the predetermined time from the start of the defect zone, inverting most significant bits of the sampled values, and integrating the sampled values including the inverted most significant bits.
15. A method of improving servo stability, comprising:
sampling the instability of the tracking error signal when a defect begins;
outputting a tracking drive signal having a phase opposite to that of the sampled tracking error signal; and
removing a DC offset generated after the defect zone ends by adding a high-frequency signal whose phase only is inverted, to a compensated tracking drive signal.
16. A method of compensating for instability of a tracking error (TE) signal, comprising:
sampling a value of the TE signal;
inverting a phase of the TE signal to yield a phase-inverted TE signal; and
using the phase-inverted TE signal as at least part of a compensated tracking drive (TRD) signal during tracking in a disc defect zone,
wherein the inverting includes:
sampling the tracking error signal generated during the predetermined time from the start of the defect zone;
inverting most significant bits of the sampled values; and
integrating the sampled values including the inverted most significant bits.
17. A method of improving servo stability, comprising:
sampling values of a TE signal;
inverting a phase of the TE signal to yield a phase-inverted TE signal by inverting most significant bits of the sampled values and integrating the sampled values including the inverted most significant bits; and
using the phase-inverted TE signal as at least part of a compensated tracking drive (TRD) signal during tracking in a disc defect zone.
18. A method of removing a DC offset generated right after a defect zone ends, comprising:
inverting a phase of a high-frequency signal to yield a phase-inverted high-frequency signal; and
adding the phase-inverted high-frequency signal a compensated tracking drive (TRD) signal.