1. A digital filter for filtering sample data, comprising:
a delay network for delaying input sample data to provide a plurality of delayed sample data outputs;
a filter network representable by a decomposed coefficient weighting matrix for processing said delayed sample data outputs; and
a processor for producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix, said processor being responsive to a sample spatial position index signal in producing said filtered output.
2. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix comprises a structurally factored matrix.
3. A digital filter according to claim 2, wherein
said structurally factored matrix employs a factor derived based on a property including at least one of, (a) coefficient matrix row symmetry, and (b) coefficient matrix column symmetry.
4. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix is derived by at least one of (a) factoring a first coefficient weighting matrix with a common row factor, and (b) factoring a first coefficient weighting matrix based on at least one of, (i) coefficient matrix row symmetry, and (ii) coefficient matrix column symmetry.
5. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix is derived by factoring a first coefficient weighting matrix using a sparse matrix.
6. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix represents a multiple input, multiple output, filter network.
7. A digital filter according to claim 1, including
an interpolation network for interpolating sample data to provide said input sample data.
8. A digital filter according to claim 1, wherein
said processor includes a factor combiner for deriving a weighted sum of factors representing a linear transform process.
9. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix exhibits the form
0
0
3
0
–
1
4
–
2
–
1
1
–
1
–
1
1
3
.
10. A digital filter according to claim 1, wherein
said digital filter provides the function
H
\u2061
(
z
)
=
1
\u03bc
\u03bc
2
\xb7
0
0
3
0
–
1
4
–
2
–
1
1
–
1
–
1
1
3
\xb7
1
z
–
1
z
–
2
z
–
3
\u2003where u is a sample spatial position representative signal and z represents an input sample.
11. A digital filter according to claim 1, wherein
said decomposed coefficient weighting matrix exhibits the form
6
58
58
6
23
59
–
59
–
23
31
–
31
–
31
31
16
–
48
48
–
16
128
.
12. A digital filter according to claim 1, wherein
said digital filter provides the following function, where u is a sample spatial position representative signal and z presents an input sample
H
\u2061
(
z
)
=
1
\u03bc
\u03bc
2
\u03bc
3
\u2061
1
2
0
3
64
0
0
1
0
23
128
0
0
31
128
0
0
0
0
1
8
\xb7
0
1
1
0
0
1
–
1
0
1
–
1
–
1
1
1
–
3
3
–
1
\xb7
1
z
–
1
z
–
2
z
–
3
13. A method for filtering sample data, comprising the steps of:
delaying input sample data to provide a plurality of delayed sample data outputs;
processing said delayed sample data outputs using a filter network represented by a structurally factored coefficient weighting matrix, said structurally factored matrix comprising a coefficient weighting matrix employing factors derived based on a property including at least one of, (a) coefficient matrix row symmetry, and (b) coefficient matrix column symmetry; and
producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix.
14. A method for filtering sample data, comprising the steps of:
delaying input sample data to provide a plurality of delayed sample data outputs;
processing said delayed sample data outputs using a filter network represented by a structurally factored coefficient weighting matrix, said structurally factored matrix being derived by at least one of (a) factoring a first coefficient weighting matrix with a common row factor, and (b) factoring a first coefficient weighting matrix based on a property including at least one of, (i) coefficient matrix row symmetry, and (ii) coefficient matrix column symmetry; and
producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix.
15. A method for filtering sample data, comprising the steps of:
delaying input sample data to provide a plurality of delayed sample data outputs;
processing said delayed sample data outputs using a filter network represented by a structurally factored coefficient weighting matrix, said structurally factored matrix comprising a decomposed coefficient weighting matrix derived by factoring a first coefficient weighting matrix using a sparse matrix; and
producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix.
16. A method for filtering sample data, comprising the steps of:
delaying input sample data to provide a plurality of delayed sample data outputs;
processing said delayed sample data outputs using a filter network using a coefficient weighting matrix comprising,
0
0
3
0
–
1
4
–
2
–
1
1
–
1
–
1
1
3
;
and
producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix.
17. A method for filtering sample data, comprising the steps of:
delaying input sample data to provide a plurality of delayed sample data outputs;
processing said delayed sample data outputs using a filter network using a coefficient weighting matrix comprising,
6
58
58
6
23
59
–
59
–
23
31
–
31
–
31
31
16
–
48
48
–
16
128
;
and
producing a filtered output by computing a weighted product summation of said delayed sample data outputs and said coefficient weighting matrix.
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 system for recovery of thermal energy from a kiln for power generation, comprising:
a kiln;
a waste heat recovery circuit including a boiler and a steam turbine, said boiler for receiving offgas from said kiln and generating steam for said turbine; and
a dry scrubber for receiving cooled offgas at a temperature from said boiler suitable for optimizing scrubber efficiency.
2. The system as set forth in claim 1, wherein said kiln is a lime kiln.
3. The system as set forth in claim 1, wherein said kiln is a cement kiln.
4. The system as set forth in claim 1, wherein said system further includes a condenser and cooling tower.