1. A computer program protect for dropout detection in a read channel, the computer program product comprising a computer readable storage medium having program code embodied therewith, the embedded program code being readable andor executable by a processor to:
execute dropout detection on a block of signal samples to detect one or more dropout events employing a set of decisions provided by a detector executing a detection algorithm;
determine an approximate location for each of the one or more detected dropout events;
statistically characterize e one or more detected dropout events to calculate one or more dropout profiles; and
selectively filter the block of signal samples during a duration of each of the detected dropout events.
2. The computer program product as recited in claim 1, wherein the embedded program code configured to selectively filter the block of signal samples is configured to cause the processor to selectively apply one or more compensation filters from a bank of compensation filters, each compensation filter corresponding to one of the one or more dropout profiles, wherein the one or more compensation filters are selected from the bank of compensation filters based on the one or more detected dropout events.
3. The computer program product as recited in claim 2, wherein the embedded program code configured to statistically characterize the one or more detected dropout events is further configured to cause the processor to:
determine a duration of each detected dropout event;
determine a first time interval over which fading in signal amplitude occurs;
determine a second time interval over which the signal amplitude returns to a nominal value; and
calculate a dropout profile for each detected dropout event based on the duration of the detected dropout event, the first time interval, and the second time interval.
4. The computer program product as recited in claim 3, further comprising program code configured to cause the processor to classify each detected dropout event into one of a plurality of groups based on the characterization of the dropout event, each group being associated with one compensation filter of the bank of compensation filters.
5. The computer program product as recited in claim 4, wherein four or more groups are associated with four or more different compensation filters.
6. The computer program product as recited in claim 1, wherein the embedded program code configured to selectively filter the block of signal samples is configured to cause the processor to apply an adaptive filter to the block of signal samples that operates in real time, the adaptive filter utilizing a compensation filter corresponding to the one or more detected dropout events.
7. The computer program product as recited in claim 1, wherein the embedded program code configured to execute dropout detection on the block of signal samples is configured to perform at least one of: detect large attenuations in a magnitude of a signal envelope indicative of a dropout event using a rectifier and envelope tracking circuit, monitor a gain value of a fast variable gain amplifier (VGA) circuit to detect a sudden increase in the gain value indicative of a dropout event, and monitor for a loss of reliability of soft information provided by a soft detector andor a soft decoder consistently over a predetermined time interval indicative of a dropout event.
8. A system for dropout detection in a read channel, the system comprising a processor and logic integrated with andor executable by the processor, the logic being configured to:
execute dropout detection on a block of signal samples to detect one or more dropout events employing a set of decisions provided by a detector executing a detection algorithm;
determine an approximate location for each of the one or more detected dropout events;
statistically characterize the one or more detected dropout events to calculate one or more dropout profiles; and
selectively filter the block of signal samples during a duration of each of the detected dropout events.
9. The system as recited in claim 8, wherein the logic configured to selectively filter the block of signal samples is further configured to selectively apply one or more compensation filters from a bank of compensation filters, each compensation filter corresponding to one of the one or more dropout profiles, wherein the one or more compensation filters are selected from the bank of compensation filters based on the one or more detected dropout events.
10. The system as recited in claim 9, wherein the logic configured to statistically characterize the one or more detected dropout events is further configured to:
determine a duration of each detected dropout event;
determine a first time interval over which fading in signal amplitude occurs;
determine a second time interval over which the signal amplitude returns to a nominal value; and
calculate a dropout profile for each detected dropout event based on the duration of the detected dropout event, the first time interval, and the second time interval.
11. The system as recited in claim 10, further comprising logic configured to classify each detected dropout event into one of a plurality of groups based on the characterization of the dropout event, each group being associated with one compensation fitter of the bank of compensation filters.
12. The system as recited in claim 11, wherein four or more groups are associated with four or more different compensation filters.
13. The system as recited in claim 8, wherein the logic configured to execute dropout detection on the block of signal samples is further configured to perform at least one of: detect large attenuations iii a magnitude of a signal envelope indicative of a dropout event using a rectifier and envelope tracking circuit, monitor a gain value of a fast variable gain amplifier (VGA) circuit to detect a sudden increase in the gain value indicative of a dropout event, and monitor for a loss of reliability of soft information provided by a soft detector andor a soft decoder consistently over a predetermined time interval indicative of a dropout event.
14. The system as recited in claim 8, wherein the logic is further configured to:
execute one or more additional digital front-end (DFE) functions on the block of signal samples employing the set of decisions provided by the detector executing the detection algorithm; and
execute a decoding algorithm of an error correcting code (ECC) on the block of signal samples using a decoder employing the set of decisions provided by the detector to generate a set of decisions provided by the decoder.
15. The system as recited in claim 14, wherein the detector is a soft detector which produces a set of soft decisions, wherein the decoder is a soft decoder which produces a set of soft decisions, and wherein the decoding algorithm is a low-density parity-check (LDPC) algorithm that produces soft decisions.
16. The system as recited in claim 14, wherein the dropout detection is executed using decisions from the detector in a first pass, and decisions from the decoder on the signal samples of a previous pass in each subsequent pass.
17. The system as recited in claim 8, wherein the logic configured to selectively filter the block of signal samples is configured to apply an adaptive filter to the block of signal samples that operates in real time, the adaptive filter utilizing a compensation filter corresponding to the one or more detected dropout events.
18. The system as recited in claim 17, wherein the logic configured to statistically characterize the one or more detected dropout events is further configured to:
determine a duration of each detected dropout event;
determine a first time interval over which fading in signal amplitude occurs;
determine a second time interval over which the signal amplitude returns to a nominal value; and
calculate a dropout profile for each detected dropout event based on the duration of the detected dropout event, the first time interval, and the second time interval.
19. A method for dropout detection in a read channel, the method comprising:
executing dropout detection on a block of signal samples to detect one or more dropout events employing a set of decisions provided by a detector executing a detection algorithm;
determining an approximate location for each of the one or more detected dropout events;
statistically characterizing the one or more detected dropout events to calculate one or more dropout profiles; and
selectively filtering the block of signal samples during a duration of each of the detected dropout events.
20. The method as recited in claim 19, wherein statistically characterizing the one or more detected dropout events comprises:
determining a duration of each detected dropout event;
determining a first time interval over which fading in signal amplitude occurs;
determining a second time interval over which the signal amplitude returns to a nominal value; and
calculating a dropout profile for each detected dropout event based on the duration of the detected dropout event, the first time interval, and the second time interval.
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 wind instrument having a neck coupled to a body tube, in which a column of air may be vibrated to produce sound, wherein the neck comprises:
a tenon for coupling with the body tube;
a interior arc region of the neck;
an octave hole located on the interior arc region; and
a key mechanism used to selectively uncover the octave hole; wherein the key mechanism, comprises:
a first lever, with an octave key on one end thereof, a contact point on another end thereof, and a pivot point between the octave key and the contact point, around which the first lever has rotational freedom; and
a second lever, with a contact point on one end thereof, contacting the contact point of the first lever, an octave hole cover on the other end thereof positioned to cover the octave hole, and a pivot point between the contact point and the octave hole cover, around which the second lever has rotational freedom.
2. The wind instrument of claim 1, wherein the key mechanism includes a biasing mechanism for biasing the octave hole cover toward the octave hole.
3. The wind instrument of claim 1, wherein the octave key couples to an octave key mechanism of a body tube of the wind instrument.
4. The wind instrument of claim 1, wherein the first lever further comprises a clasp for contacting the second lever on two points.
5. The wind instrument of claim 1, wherein the instrument is one selected from the group consisting of: arghul, aulochrome, basset horn, clarinet, E-flat clarinet, alto clarinet, bass clarinet, contra-alto clarinet, contrabass clarinet, launeddas, mijwiz, rothphone, sarrusophone, saxophone, soprillo, sopranino saxophone, soprano saxophone, alto saxophone, tenor saxophone, C melody saxophone, baritone saxophone, bass saxophone, contrabass saxophone, subcontrabass saxophone, tubax, t\xe1rog\xe1to, bassanelli, bassoon, contrabassoon, bombarde, duduk, dulcian, dulzania, guan, heckelphone, piccolo heckelphone, hojok, mizmar, nadaswaram, oboe, piccolo oboe, oboe d’amore, English horn, oboe da caccia, racket, shawm, shehnai, suona, surnay, tromboon, trompeta china, zuma, bagpipes, cornamuse, crumhorn, hirtenschalmei, kortholt, rauschpfeife, bansuri, flute, fife, piccolo, Western concert flute, alto flute, bass flute, contrabass flute, ryuteki, hocchiku, kaval, ney, quena, shakuhachi, flageolet, gemshorn, ocarina, recorder, tin whistle, penny whistle, tonette, trumpet, bass trumpet, flumpet, French horn, tuba, Wagner tuba, trombone, superbone, bugle, sousaphone, mellophone, euphonium, flugelborn, saxhorn, cornet, cornetto, serpent, sackbut, bazooka, horn, ophicleide, didgeridoo, shofar, conch alphorn, cimbasso, and keyed trumpet.
6. The wind instrument of claim 1, wherein the wind instrument is a saxophone.
7. The wind instrument of claim 1, wherein the neck includes a cross section that is substantially circular.
8. The wind instrument of claim 1, wherein the interior arc region includes no greater than 180\xb0 of a circumference of the substantially circular cross section of the body.
9. The wind instrument of claim 1, wherein the interior arc region includes no greater than 120\xb0 of a circumference of the substantially circular cross section of the body.
10. The wind instrument of claim 2, wherein the biasing mechanism includes a spring.
11. The wind instrument of claim 10, wherein the spring includes a first end contacting a pivot support or a lower surface of a neck of the wind instrument.
12. The wind instrument of claim 10, wherein the spring includes a second end contacting a point of lever between the pivot point and the octave key.
13. The wind instrument of claim 10, wherein the biasing mechanism disposes the octave key toward or away from the lower surface of the neck of the wind instrument.
14. The wind instrument of claim 1, wherein the octave hole is positioned on the lower surface of the neck of the wind instrument.
15. The wind instrument of claim 6, wherein the saxophone is a soprano saxophone.
16. The wind instrument of claim 1, wherein the octave hole cover includes a pad that conforms to the shape of the octave hole.
17. The wind instrument of claim 1, wherein the second lever includes an angled portion between the pivot point and the octave hole cover.
18. The wind instrument of claim 17, wherein the angled portion slopes towards the lower surface of the neck of the wind instrument.
19. The wind instrument of claim 18, wherein the angled portion is not parallel to the lower surface of the neck of the wind instrument when the octave hole cover is positioned on the octave hole.