Methods and apparatus for improved pattern detection
Improved pattern detection is provided for a predefined pattern in data. A detection threshold employed by a Euclidean detector to detect a pattern (such as a Servo Address Mark) may be adjusted based upon data gathered that corresponds to an indication of a detected pattern by one of a plurality of pattern detectors.
1. A pattern detection system, the system comprising:
a first pattern detector circuit to apply a first pattern detection algorithm to:
a first portion of a data input to yield a first detected pattern indicator; and
a second portion of the data input to yield a second pattern indicator;
a second pattern detector circuit to apply a second pattern detection algorithm to:
the first portion of the data input using an adapted threshold to yield a first pattern value and a third detected pattern indicator;
the second portion of the data input using the adapted threshold to yield a second pattern value and a fourth detected pattern indicator;
a memory circuit to:
store the first pattern value when at least one of the first detected pattern indicator or the third detected pattern indicator indicates a found pattern; and
store the second pattern value when at least one of the second detected pattern indicator or the fourth detected pattern indicator indicates a found pattern.
2. The system of claim 1 , the system further comprising: a threshold adaptation circuit to adapt the adapted threshold using the first pattern value from the memory circuit and the second pattern value from the memory circuit.
3. The system of claim 2 , wherein threshold adaptation circuit is to: calculate a difference between the first pattern value and the second pattern value; multiply the difference by a gain to yield a product; and summing the product with the first pattern value to yield the adapted threshold.
4. The system of claim 3 , wherein the gain is a value between zero and one.
5. The system of claim 3 , wherein the gain is a configurable value.
6. The system of claim 3 , wherein the first pattern value is a maximum identified Euclidean distance value, and second pattern value is a minimum identified Euclidean distance value.
7. The system of claim 1 , wherein the first pattern detector circuit is a Hamming detector circuit, and wherein the first pattern detection algorithm is a Hamming distance determination algorithm.
8. The system of claim 7 , wherein the Hamming distance determination algorithm includes: calculating a first Hamming distance between the first portion of the data input and a predefined pattern; calculating a second Hamming distance between the second portion of the data input and the predefined pattern; asserting the first detected pattern indicator when the first Hamming distance is less than a predefined threshold; and asserting the second detected pattern indicator when the second Hamming distance is less than the predefined threshold.
9. The system of claim 8 , wherein the second pattern detector circuit is a Euclidean distance based detector circuit, wherein the first pattern value is a first Euclidean distance between the first portion and the predefined pattern, wherein the second pattern value is a second Euclidean distance between the second portion and the predefined pattern.
10. The system of claim 9 , wherein the second pattern detection algorithm is a Euclidean distance determination algorithm that includes: calculating the first Euclidean distance between the first portion of the data input and the predefined pattern; calculating the second Euclidean distance between the second portion of the data input and the predefined pattern; asserting the third detected pattern indicator when the first Euclidean distance is less than the adapted threshold; and asserting the fourth detected pattern indicator when the second Euclidean distance is less than the adapted threshold.
11. The system of claim 1 , wherein the second pattern detector circuit is a Euclidean distance based detector circuit, wherein the first pattern value is a first Euclidean distance between the first portion and the predefined pattern, wherein the second pattern value is a second Euclidean distance between the second portion and the predefined pattern, and wherein the second pattern detection algorithm is a Euclidean distance determination algorithm that includes: calculating the first Euclidean distance between the first portion of the data input and the predefined pattern; calculating the second Euclidean distance between the second portion of the data input and the predefined pattern; asserting the third detected pattern indicator when the first Euclidean distance is less than the adapted threshold; and asserting the fourth detected pattern indicator when the second Euclidean distance is less than the adapted threshold.
12. The system of claim 1 , wherein the system is implemented in an integrated circuit.
13. The system of claim 1 , wherein the predefined pattern is selected from a group consisting of: a servo address mark; a repeatable run out address mark; an image pattern; an antenna signal pattern; and a combination of a servo address mark and a repeatable run out address mark.
14. The system of claim 1 , the system further comprising: a storage medium, wherein the data input is derived from the storage medium.
15. A method for pattern detection, the method comprising: applying a first pattern detection algorithm to a first portion of a data input to determine a first detected pattern indicator; applying the first pattern detection algorithm to a second portion of the data input to determine a second detected pattern indicator; using a pattern detector circuit applying a second pattern detection algorithm to: the first portion of the data input using an adapted threshold to yield a first pattern value and a third detected pattern indicator; and the second portion of the data input using the adapted threshold to yield a second pattern value and a fourth detected pattern indicator; and adapting the adapted threshold using: the first pattern value when at least one of the first detected pattern indicator or the third detected pattern indicator is asserted; and the second pattern value when at least one of the second detected pattern indicator or the fourth detected pattern indicator is asserted.
16. The method of claim 15 , wherein the first pattern detection algorithm includes: calculating a first Hamming distance between the first portion of the data input and a predefined pattern; calculating a second Hamming distance between the second portion of the data input and the predefined pattern; asserting the first detected pattern indicator when the first Hamming distance is less than a predefined threshold; and asserting the second detected pattern indicator when the second Hamming distance is less than the predefined threshold.
17. The method of claim 16 , wherein the pattern detector circuit is a Euclidean distance based detector circuit, wherein the first pattern value is a first Euclidean distance between the first portion and the predefined pattern, wherein the second pattern value is a second Euclidean distance between the second portion and the predefined pattern; and wherein the second pattern detection algorithm includes: calculating the first Euclidean distance between the first portion of the data input and the predefined pattern; calculating the second Euclidean distance between the second portion of the data input and the predefined pattern; asserting the third detected pattern indicator when the first Euclidean distance is less than the adapted threshold; and asserting the fourth detected pattern indicator when the second Euclidean distance is less than the adapted threshold.
18. The method of claim 15 , wherein adapting the adapted threshold includes: calculating a difference between the first pattern value and the second pattern value; multiplying the difference by a gain to yield a product; and summing the product with the first pattern value to yield the adapted threshold.
19. The method of claim 18 , wherein the gain is a value between zero and one.
20. The method of claim 19 , wherein the first pattern value is a maximum identified Euclidean distance value, and second pattern value is a minimum identified Euclidean distance value.
21. The method of claim 20 , the method further comprising: configuring the gain.
22. The method of claim 15 , wherein the pattern detector circuit is a Euclidean distance based detector circuit, wherein the first pattern value is a first Euclidean distance between the first portion and the predefined pattern, wherein the second pattern value is a second Euclidean distance between the second portion and the predefined pattern, and wherein the second pattern detection algorithm is a Euclidean distance determination algorithm that includes: calculating the first Euclidean distance between the first portion of the data input and the predefined pattern; calculating the second Euclidean distance between the second portion of the data input and the predefined pattern; asserting the third detected pattern indicator when the first Euclidean distance is less than the adapted threshold; and asserting the fourth detected pattern indicator when the second Euclidean distance is less than the adapted.