1. A digital game scouting camera, comprising:
a digital camera for taking an image, said camera enclosed in a camera housing;
an electromechanical device comprising a primary magnet and a support element having a secondary magnet, and said support element pivotally secured to said electromechanical device about a pivot axis; and
an optical lens filter;
wherein said primary magnet opposes said secondary magnet to pivot said support element about said pivot axis to selectively insert said optical lens filter into an optical path of said camera.
2. The camera of claim 1 wherein said camera housing is weatherproof and constructed from an impact resistant plastic.
3. The camera of claim 1 wherein said camera housing further comprises a main body and a removable cover.
4. The camera of claim 1 wherein said primary magnet is an electromagnet comprising an electromagnetically inductive coil wound around a bobbin, said bobbin having an axial channel with an armature disposed therein.
5. The camera of claim 4 wherein said axial channel of said bobbin is substantially perpendicular to said pivot axis of said support element.
6. The camera of claim 4 wherein said armature further comprises a pair of pole pieces directing the magnetic field generated by said electromagnet towards said secondary magnet.
7. The camera of claim 6 wherein said secondary magnet is a permanent magnet.
8. The camera of claim 7 wherein said pole pieces are aligned generally parallel with the axis passing through the magnetic poles of said permanent magnet.
9. The camera of claim 4 wherein said armature is constructed of a ferromagnetic metal or a ferromagnetic compound.
10. The camera of claim 1 wherein said support element further comprises a body having opposing trunnions rotatably engaged with said electromechanical device, and said support element further comprises a cantilevered filter arm.
11. The camera of claim 10 wherein said opposing trunnions are axially spaced and coaxially aligned along said pivot axis.
12. The camera of claim 10 wherein said filter arm further comprises a pocket into which said optical lens filter is slidably disposed and secured.
13. The camera of claim 12 wherein said support element further comprises a limiting arm projecting in a direction opposing said filter arm, said limiting arm engaged with a generally U-shaped stopping element.
14. The camera of claim 13 wherein said limiting arm is disposed intermediate of upturned arms of said stopping element.
15. The camera of claim 10 wherein said filter arm further comprises an outer periphery having at least one tab and a shoulder for retaining said optical lens filter.
16. The camera of claim 15 further comprising a pair of stopping elements disposed at opposing sides of a device housing.
17. The camera of claim 10 wherein said filter arm further comprises an elongated shaft.
18. The camera of claim 17 wherein said shaft is engaged with a filter bracket retaining said optical lens filter.
19. The camera of claim 1 wherein said electromechanical device further comprises a device housing and a housing coverplate.
20. The camera of claim 19 wherein said device housing and said housing coverplate each further comprise an optical path aperture axially aligned along said optical path of said camera.
21. The camera of claim 19 wherein said device housing further comprises a two-part device housing.
22. The camera of claim 21 wherein said two-part device housing further comprises:
a first housing part having a trunnion support; and
a second housing part joined to said first housing part, said second housing part having a trunnion support, a generally arcuate channel and an optical path aperture.
23. The camera of claim 1 wherein said secondary magnet is a permanent magnet.
24. The camera of claim 23 wherein said support element further comprises a pair of opposing trunnions protruding from a main body having an internal cavity, and said trunnions being axially spaced and coaxially aligned along said pivot axis.
25. The camera of claim 24 wherein said permanent magnet is retained within said internal cavity of said main body and is intermediate of said opposing trunnions.
26. The camera of claim 25 wherein said pivot axis is generally aligned intermediate of the magnetic poles of said permanent magnet.
27. An electromechanical device for selectively inserting an optical lens filter into an optical path of a digital camera, said electromechanical device comprising:
a device housing having a housing coverplate removably attached thereto;
an electromagnet comprising an electromagnetically inductive coil wound around a bobbin, and said bobbin having an axial channel with an armature disposed therein;
a support element comprising a body and a cantilevered filter arm, said body further comprising a magnet and opposing trunnions axially spaced and coaxially aligned along an axis; and
at least one optical lens filter engaged with said filter arm of said support element;
wherein opposing magnetic fields generated by said electromagnet and said magnet pivot said support element about said axis to selectively move said optical lens filter.
28. The electromechanical device of claim 27 wherein said axial channel of said bobbin is substantially perpendicular to said pivot axis.
29. The electromechanical device of claim 27 wherein said armature is generally U-shaped and further comprises a pair of pole pieces directing the magnetic field generated by said electromagnet towards said magnet.
30. The electromechanical device of claim 27 wherein said armature is constructed of a ferromagnetic metal or a ferromagnetic compound.
31. The electromechanical device of claim 27 wherein said magnet is a permanent magnet.
32. The electromechanical device of claim 27 wherein said opposing trunnions are rotatably engaged with said device housing and said housing coverplate.
33. The electromechanical device of claim 27 wherein said device housing is a two-part device housing comprising a first housing part and a second housing part.
34. The electromechanical device of claim 33 wherein said opposing trunnions are rotatably engaged with trunnion supports of said two-part device housing.
35. The electromechanical device of claim 33 further comprising a filter bracket slidably engaged with said two-part device housing.
36. The electromechanical device of claim 27 further comprising a filter bracket retaining said optical lens filter.
37. The electromechanical device of claim 36 wherein said filter arm further comprises an elongated shaft engaged with said filter bracket.
38. The electromechanical device of claim 27 further comprising a stopping element disposed within said device housing.
39. The electromechanical device of claim 38 wherein said support element further comprises a limiting arm projecting in a direction opposing said cantilevered filter arm, and said limiting arm engaged with said stopping element.
40. The electromechanical device of claim 39 wherein said stopping element is a plurality of stopping elements each disposed within said device housing.
41. The electromechanical device of claim 27 wherein said filter arm further comprises an outer periphery having at least one tab and a shoulder for retaining said optical lens filter.
42. The electromechanical device of claim 27 wherein said device housing and said housing coverplate each have an optical path aperture.
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. An apparatus comprising:
at least one processor configured to filter a sequence of input values with an infinite impulse response (IIR) filter having at least one coefficient to obtain a sequence of output values, and to derive a sequence of predicted values based on the sequence of input values, to determine prediction errors between a sequence of predicted values and the sequence of input values, to filter the determined prediction errors, to calculate a partial derivative term based on the determined prediction errors and filtered determined prediction errors, and to update the at least one coefficient based on the partial derivative term; and
a memory coupled to the at least one processor, wherein the at least one processor is configured to filter the sequence of input values with multiple prediction filters to obtain multiple sequences of predicted values, each prediction filter having a different set of at least one coefficient, to identify a prediction filter with a smallest prediction error among the multiple prediction filters, and to filter the sequence of input values using the set of at least one coefficient for the identified prediction filter.
2. The apparatus of claim 1, wherein the at least one processor is configured to compute errors between the sequence of input values and the sequence of predicted values for each prediction filter, to determine a mean square error for each prediction filter based on the errors for the prediction filter, and to identify the prediction filter with a smallest mean square error.
3. The apparatus of claim 1, wherein each prediction filter has a single coefficient, and wherein the multiple prediction filters have different coefficients.
4. The apparatus of claim 1, wherein the at least one processor is further configured to select and output the sequence of predicted values from the identified prediction filter as a filtered channel impulse response estimate.
5. The apparatus of claim 1, wherein the processor is configured to filter the determined prediction errors using a coefficient of the IIR.
6. A method comprising:
filtering a sequence of input values with an infinite impulse response (IIR) filter having at least one coefficient to obtain a sequence of output values;
deriving a sequence of predicted values based on the sequence of input values;
determining prediction errors between the sequence of predicted values and the sequence of input values;
filtering the determined prediction errors;
calculating a partial derivative term based on the determined prediction errors and filtered determined prediction errors; and
updating the at least one coefficient based on the partial derivative term, wherein the updating the at least one coefficient comprises:
filtering the sequence of input values with multiple prediction filters to obtain multiple sequences of predicted values, each prediction filter having a different set of at least one coefficient,
identifying a prediction filter with a smallest prediction error among the multiple prediction filters, and
selecting the set of at least one coefficient for the identified prediction filter as the at least one coefficient.
7. The method of claim 6, wherein the identifying the prediction filter with the smallest prediction error comprises:
computing errors between the sequence of input values and the sequence of predicted values for each prediction filter,
determining a mean square error for each prediction filter based on the errors for the prediction filter, and
identifying the prediction filter with a smallest mean square error.
8. The method of claim 6, wherein each prediction filter has a single coefficient.
9. The method of claim 6, further comprising selecting and outputting the sequence of predicted values from the identified prediction filter as a filtered channel impulse response estimate.
10. The method of claim 6, wherein filtering the determined prediction errors comprises using a coefficient of the IIR.
11. An apparatus comprising:
means for filtering a sequence of input values with an infinite impulse response (IIR) filter having at least one coefficient to obtain a sequence of output values;
means for deriving a sequence of predicted values based on the sequence of input values;
means for determining prediction errors between the sequence of predicted values and the sequence of input values;
means for filtering the determined prediction errors;
means for calculating a partial derivative term based on the determined prediction errors and filtered determined prediction errors; and
means for updating the at least one coefficient based on the partial derivative term, wherein the means for updating the at least one coefficient comprises:
means for filtering the sequence of input values with multiple prediction filters to obtain multiple sequences of predicted values, each prediction filter having a different set of at least one coefficient,
means for identifying a prediction filter with a smallest prediction error among the multiple prediction filters, and
means for selecting the set of at least one coefficient for the identified prediction filter as the at least one coefficient.
12. The apparatus of claim 11, wherein the means for identifying the prediction filter with the smallest prediction error comprises:
means for computing errors between the sequence of input values and the sequence of predicted values for each prediction filter,
means for determining a mean square error for each prediction filter based on the errors for the prediction filter, and
means for identifying the prediction filter with a smallest mean square error.
13. The apparatus of claim 11, wherein each prediction filter has a single coefficient.
14. The apparatus of claim 11, further comprising means for selecting and outputting the sequence of predicted values from the identified prediction filter as a filtered channel impulse response estimate.
15. The apparatus of claim 11, wherein the means for filtering the determined prediction errors are configured to use a coefficient of the IIR to filter the determined prediction errors.
16. A non-transitory processor-readable medium comprising processor-readable instructions configured to cause a processor to:
filter a sequence of input values with an infinite impulse response (IIR) filter having at least one coefficient to obtain a sequence of output values;
derive a sequence of predicted values based on the sequence of input values;
determine prediction errors between the sequence of predicted values and the sequence of input values;
filter the determined prediction errors;
calculate a partial derivative term based on the determined prediction errors and filtered determined prediction errors; and
update the at least one coefficient based on the partial derivative term, wherein the updating the at least one coefficient comprises:
filter the sequence of input values with multiple prediction filters to obtain multiple sequences of predicted values, each prediction filter having a different set of at least one coefficient,
identify a prediction filter with a smallest prediction error among the multiple prediction filters, and
select the set of at least one coefficient for the identified prediction filter as the at least one coefficient.
17. The non-transitory processor-readable medium of claim 16, wherein the instructions configured to cause the processor to identify the prediction filter with the smallest prediction error are configured to cause the processor to:
compute errors between the sequence of input values and the sequence of predicted values for each prediction filter,
determine a mean square error for each prediction filter based on the errors for the prediction filter, and
identify the prediction filter with a smallest mean square error.
18. The non-transitory processor-readable medium of claim 16, further comprising instructions configured to cause the processor to select and output the sequence of predicted values from the identified prediction filter as a filtered channel impulse response estimate.
19. An apparatus comprising:
a memory; and
a processor coupled to the memory and configured to:
filter a sequence of input values with an infinite impulse response (IIR) filter using a first coefficient to obtain a sequence of output values;
derive multiple sequences of predicted values based on the sequence of input values by filtering the sequence of input values with multiple prediction filters each using a different second coefficient;
determine prediction errors between the sequences of predicted values and the sequence of input values;
filter the determined prediction errors;
calculate a partial derivative term based on the determined prediction errors and the filtered determined prediction errors; and
update the first coefficient based on the partial derivative term.
20. The apparatus of claim 19 wherein the processor is further configured to:
identify which of the multiple sequences of predicted values has a smallest prediction error; and
filter the sequence of input values using the second coefficient corresponding to the sequence of predicted values with the smallest prediction error.