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src/DLD-FUNCTIONS/filter.cc

changeset 9846: 1d90fc211872
parent:8cc2d087f3c1
author: John W. Eaton <jwe@octave.org>
date: Sat Nov 21 21:44:51 2009 -0500 (33 hours ago)
permissions: -rw-r--r--
description: configure.ac: report freetype, fontconfig, and fltk cflags and libs info
1/*
2
3Copyright (C) 1996, 1997, 1999, 2000, 2002, 2004, 2005, 2006, 2007,
4 2008, 2009 John W. Eaton
5
6This file is part of Octave.
7
8Octave is free software; you can redistribute it and/or modify it
9under the terms of the GNU General Public License as published by the
10Free Software Foundation; either version 3 of the License, or (at your
11option) any later version.
12
13Octave is distributed in the hope that it will be useful, but WITHOUT
14ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
15FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
16for more details.
17
18You should have received a copy of the GNU General Public License
19along with Octave; see the file COPYING. If not, see
20<http://www.gnu.org/licenses/>.
21
22*/
23
24// Based on Tony Richardson's filter.m.
25//
26// Originally translated to C++ by KH (Kurt.Hornik@wu-wien.ac.at)
27// with help from Fritz Leisch and Andreas Weingessel on Oct 20, 1994.
28//
29// Rewritten to use templates to handle both real and complex cases by
30// jwe, Wed Nov 1 19:15:29 1995.
31
32#ifdef HAVE_CONFIG_H
33#include <config.h>
34#endif
35
36#include "quit.h"
37
38#include "defun-dld.h"
39#include "error.h"
40#include "oct-obj.h"
41
42#if !defined (CXX_NEW_FRIEND_TEMPLATE_DECL)
43extern MArrayN<double>
44filter (MArray<double>&, MArray<double>&, MArrayN<double>&, int dim);
45
46extern MArrayN<Complex>
47filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&, int dim);
48
49extern MArrayN<float>
50filter (MArray<float>&, MArray<float>&, MArrayN<float>&, int dim);
51
52extern MArrayN<FloatComplex>
53filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&, int dim);
54#endif
55
56template <class T>
57MArrayN<T>
58filter (MArray<T>& b, MArray<T>& a, MArrayN<T>& x, MArrayN<T>& si,
59 int dim = 0)
60{
61 MArrayN<T> y;
62
63 octave_idx_type a_len = a.length ();
64 octave_idx_type b_len = b.length ();
65
66 octave_idx_type ab_len = a_len > b_len ? a_len : b_len;
67
68 b.resize (ab_len, 0.0);
69 if (a_len > 1)
70 a.resize (ab_len, 0.0);
71
72 T norm = a (0);
73
74 if (norm == static_cast<T>(0.0))
75 {
76 error ("filter: the first element of a must be non-zero");
77 return y;
78 }
79
80 dim_vector x_dims = x.dims ();
81 if (dim < 0 || dim > x_dims.length ())
82 {
83 error ("filter: filtering over invalid dimension");
84 return y;
85 }
86
87 octave_idx_type x_len = x_dims(dim);
88
89 dim_vector si_dims = si.dims ();
90 octave_idx_type si_len = si_dims(0);
91
92 if (si_len != ab_len - 1)
93 {
94 error ("filter: first dimension of si must be of length max (length (a), length (b)) - 1");
95 return y;
96 }
97
98 if (si_dims.length () != x_dims.length ())
99 {
100 error ("filter: dimensionality of si and x must agree");
101 return y;
102 }
103
104 octave_idx_type si_dim = 0;
105 for (octave_idx_type i = 0; i < x_dims.length (); i++)
106 {
107 if (i == dim)
108 continue;
109
110 if (x_dims(i) == 1)
111 continue;
112
113 if (si_dims(++si_dim) != x_dims(i))
114 {
115 error ("filter: dimensionality of si and x must agree");
116 return y;
117 }
118 }
119
120 if (norm != static_cast<T>(1.0))
121 {
122 a = a / norm;
123 b = b / norm;
124 }
125
126 if (a_len <= 1 && si_len <= 0)
127 return b(0) * x;
128
129 y.resize (x_dims, 0.0);
130
131 int x_stride = 1;
132 for (int i = 0; i < dim; i++)
133 x_stride *= x_dims(i);
134
135 octave_idx_type x_num = x_dims.numel () / x_len;
136 for (octave_idx_type num = 0; num < x_num; num++)
137 {
138 octave_idx_type x_offset;
139 if (x_stride == 1)
140 x_offset = num * x_len;
141 else
142 {
143 octave_idx_type x_offset2 = 0;
144 x_offset = num;
145 while (x_offset >= x_stride)
146 {
147 x_offset -= x_stride;
148 x_offset2++;
149 }
150 x_offset += x_offset2 * x_stride * x_len;
151 }
152 octave_idx_type si_offset = num * si_len;
153
154 if (a_len > 1)
155 {
156 T *py = y.fortran_vec ();
157 T *psi = si.fortran_vec ();
158
159 const T *pa = a.data ();
160 const T *pb = b.data ();
161 const T *px = x.data ();
162
163 psi += si_offset;
164
165 for (octave_idx_type i = 0, idx = x_offset; i < x_len; i++, idx += x_stride)
166 {
167 py[idx] = psi[0] + pb[0] * px[idx];
168
169 if (si_len > 0)
170 {
171 for (octave_idx_type j = 0; j < si_len - 1; j++)
172 {
173 OCTAVE_QUIT;
174
175 psi[j] = psi[j+1] - pa[j+1] * py[idx] + pb[j+1] * px[idx];
176 }
177
178 psi[si_len-1] = pb[si_len] * px[idx] - pa[si_len] * py[idx];
179 }
180 else
181 {
182 OCTAVE_QUIT;
183
184 psi[0] = pb[si_len] * px[idx] - pa[si_len] * py[idx];
185 }
186 }
187 }
188 else if (si_len > 0)
189 {
190 T *py = y.fortran_vec ();
191 T *psi = si.fortran_vec ();
192
193 const T *pb = b.data ();
194 const T *px = x.data ();
195
196 psi += si_offset;
197
198 for (octave_idx_type i = 0, idx = x_offset; i < x_len; i++, idx += x_stride)
199 {
200 py[idx] = psi[0] + pb[0] * px[idx];
201
202 if (si_len > 1)
203 {
204 for (octave_idx_type j = 0; j < si_len - 1; j++)
205 {
206 OCTAVE_QUIT;
207
208 psi[j] = psi[j+1] + pb[j+1] * px[idx];
209 }
210
211 psi[si_len-1] = pb[si_len] * px[idx];
212 }
213 else
214 {
215 OCTAVE_QUIT;
216
217 psi[0] = pb[1] * px[idx];
218 }
219 }
220 }
221 }
222
223 return y;
224}
225
226#if !defined (CXX_NEW_FRIEND_TEMPLATE_DECL)
227extern MArrayN<double>
228filter (MArray<double>&, MArray<double>&, MArrayN<double>&,
229 MArrayN<double>&, int dim);
230
231extern MArrayN<Complex>
232filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&,
233 MArrayN<Complex>&, int dim);
234
235extern MArrayN<float>
236filter (MArray<float>&, MArray<float>&, MArrayN<float>&,
237 MArrayN<float>&, int dim);
238
239extern MArrayN<FloatComplex>
240filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&,
241 MArrayN<FloatComplex>&, int dim);
242#endif
243
244template <class T>
245MArrayN<T>
246filter (MArray<T>& b, MArray<T>& a, MArrayN<T>& x, int dim = -1)
247{
248 dim_vector x_dims = x.dims();
249
250 if (dim < 0)
251 {
252 // Find first non-singleton dimension
253 while (dim < x_dims.length () && x_dims(dim) <= 1)
254 dim++;
255
256 // All dimensions singleton, pick first dimension
257 if (dim == x_dims.length ())
258 dim = 0;
259 }
260 else
261 if (dim < 0 || dim > x_dims.length ())
262 {
263 error ("filter: filtering over invalid dimension");
264 return MArrayN<T> ();
265 }
266
267 octave_idx_type a_len = a.length ();
268 octave_idx_type b_len = b.length ();
269
270 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
271 dim_vector si_dims = x.dims ();
272 for (int i = dim; i > 0; i--)
273 si_dims(i) = si_dims(i-1);
274 si_dims(0) = si_len;
275
276 MArrayN<T> si (si_dims, T (0.0));
277
278 return filter (b, a, x, si, dim);
279}
280
281DEFUN_DLD (filter, args, nargout,
282 "-*- texinfo -*-\n\
283@deftypefn {Loadable Function} {y =} filter (@var{b}, @var{a}, @var{x})\n\
284@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si})\n\
285@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, [], @var{dim})\n\
286@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si}, @var{dim})\n\
287Return the solution to the following linear, time-invariant difference\n\
288equation:\n\
289@tex\n\
290$$\n\
291\\sum_{k=0}^N a_{k+1} y_{n-k} = \\sum_{k=0}^M b_{k+1} x_{n-k}, \\qquad\n\
292 1 \\le n \\le P\n\
293$$\n\
294@end tex\n\
295@ifnottex\n\
296\n\
297@c Set example in small font to prevent overfull line\n\
298@smallexample\n\
299 N M\n\
300 SUM a(k+1) y(n-k) = SUM b(k+1) x(n-k) for 1<=n<=length(x)\n\
301 k=0 k=0\n\
302@end smallexample\n\
303@end ifnottex\n\
304\n\
305@noindent\n\
306where\n\
307@ifnottex\n\
308 N=length(a)-1 and M=length(b)-1.\n\
309@end ifnottex\n\
310@tex\n\
311 $a \\in \\Re^{N-1}$, $b \\in \\Re^{M-1}$, and $x \\in \\Re^P$.\n\
312@end tex\n\
313over the first non-singleton dimension of @var{x} or over @var{dim} if\n\
314supplied. An equivalent form of this equation is:\n\
315@tex\n\
316$$\n\
317y_n = -\\sum_{k=1}^N c_{k+1} y_{n-k} + \\sum_{k=0}^M d_{k+1} x_{n-k}, \\qquad\n\
318 1 \\le n \\le P\n\
319$$\n\
320@end tex\n\
321@ifnottex\n\
322\n\
323@c Set example in small font to prevent overfull line\n\
324@smallexample\n\
325 N M\n\
326 y(n) = - SUM c(k+1) y(n-k) + SUM d(k+1) x(n-k) for 1<=n<=length(x)\n\
327 k=1 k=0\n\
328@end smallexample\n\
329@end ifnottex\n\
330\n\
331@noindent\n\
332where\n\
333@ifnottex\n\
334 c = a/a(1) and d = b/a(1).\n\
335@end ifnottex\n\
336@tex\n\
337$c = a/a_1$ and $d = b/a_1$.\n\
338@end tex\n\
339\n\
340If the fourth argument @var{si} is provided, it is taken as the\n\
341initial state of the system and the final state is returned as\n\
342@var{sf}. The state vector is a column vector whose length is\n\
343equal to the length of the longest coefficient vector minus one.\n\
344If @var{si} is not supplied, the initial state vector is set to all\n\
345zeros.\n\
346\n\
347In terms of the z-transform, y is the result of passing the discrete-\n\
348time signal x through a system characterized by the following rational\n\
349system function:\n\
350@tex\n\
351$$\n\
352H(z) = {\\displaystyle\\sum_{k=0}^M d_{k+1} z^{-k}\n\
353 \\over 1 + \\displaystyle\\sum_{k+1}^N c_{k+1} z^{-k}}\n\
354$$\n\
355@end tex\n\
356@ifnottex\n\
357\n\
358@example\n\
359@group\n\
360 M\n\
361 SUM d(k+1) z^(-k)\n\
362 k=0\n\
363 H(z) = ----------------------\n\
364 N\n\
365 1 + SUM c(k+1) z^(-k)\n\
366 k=1\n\
367@end group\n\
368@end example\n\
369@end ifnottex\n\
370@end deftypefn")
371{
372 octave_value_list retval;
373
374 int nargin = args.length ();
375
376 if (nargin < 3 || nargin > 5)
377 {
378 print_usage ();
379 return retval;
380 }
381
382 const char *errmsg = "filter: arguments a and b must be vectors";
383
384 int dim;
385 dim_vector x_dims = args(2).dims ();
386
387 if (nargin == 5)
388 {
389 dim = args(4).nint_value() - 1;
390 if (dim < 0 || dim >= x_dims.length ())
391 {
392 error ("filter: filtering over invalid dimension");
393 return retval;
394 }
395 }
396 else
397 {
398 // Find first non-singleton dimension
399 dim = 0;
400 while (dim < x_dims.length () && x_dims(dim) <= 1)
401 dim++;
402
403 // All dimensions singleton, pick first dimension
404 if (dim == x_dims.length ())
405 dim = 0;
406 }
407
408 bool isfloat = (args(0).is_single_type ()
409 || args(1).is_single_type ()
410 || args(2).is_single_type ()
411 || (nargin >= 4 && args(3).is_single_type ()));
412
413 if (args(0).is_complex_type ()
414 || args(1).is_complex_type ()
415 || args(2).is_complex_type ()
416 || (nargin >= 4 && args(3).is_complex_type ()))
417 {
418 if (isfloat)
419 {
420 FloatComplexColumnVector b (args(0).float_complex_vector_value ());
421 FloatComplexColumnVector a (args(1).float_complex_vector_value ());
422
423 FloatComplexNDArray x (args(2).float_complex_array_value ());
424
425 if (! error_state)
426 {
427 FloatComplexNDArray si;
428
429 if (nargin == 3 || args(3).is_empty ())
430 {
431 octave_idx_type a_len = a.length ();
432 octave_idx_type b_len = b.length ();
433
434 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
435
436 dim_vector si_dims = x.dims ();
437 for (int i = dim; i > 0; i--)
438 si_dims(i) = si_dims(i-1);
439 si_dims(0) = si_len;
440
441 si.resize (si_dims, 0.0);
442 }
443 else
444 {
445 dim_vector si_dims = args (3).dims ();
446 bool si_is_vector = true;
447 for (int i = 0; i < si_dims.length (); i++)
448 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
449 {
450 si_is_vector = false;
451 break;
452 }
453
454 si = args(3).float_complex_array_value ();
455
456 if (si_is_vector)
457 si = si.reshape (dim_vector (si.numel (), 1));
458 }
459
460 if (! error_state)
461 {
462 FloatComplexNDArray y (filter (b, a, x, si, dim));
463
464 if (nargout == 2)
465 retval(1) = si;
466
467 retval(0) = y;
468 }
469 else
470 error (errmsg);
471 }
472 else
473 error (errmsg);
474 }
475 else
476 {
477 ComplexColumnVector b (args(0).complex_vector_value ());
478 ComplexColumnVector a (args(1).complex_vector_value ());
479
480 ComplexNDArray x (args(2).complex_array_value ());
481
482 if (! error_state)
483 {
484 ComplexNDArray si;
485
486 if (nargin == 3 || args(3).is_empty ())
487 {
488 octave_idx_type a_len = a.length ();
489 octave_idx_type b_len = b.length ();
490
491 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
492
493 dim_vector si_dims = x.dims ();
494 for (int i = dim; i > 0; i--)
495 si_dims(i) = si_dims(i-1);
496 si_dims(0) = si_len;
497
498 si.resize (si_dims, 0.0);
499 }
500 else
501 {
502 dim_vector si_dims = args (3).dims ();
503 bool si_is_vector = true;
504 for (int i = 0; i < si_dims.length (); i++)
505 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
506 {
507 si_is_vector = false;
508 break;
509 }
510
511 si = args(3).complex_array_value ();
512
513 if (si_is_vector)
514 si = si.reshape (dim_vector (si.numel (), 1));
515 }
516
517 if (! error_state)
518 {
519 ComplexNDArray y (filter (b, a, x, si, dim));
520
521 if (nargout == 2)
522 retval(1) = si;
523
524 retval(0) = y;
525 }
526 else
527 error (errmsg);
528 }
529 else
530 error (errmsg);
531 }
532 }
533 else
534 {
535 if (isfloat)
536 {
537 FloatColumnVector b (args(0).float_vector_value ());
538 FloatColumnVector a (args(1).float_vector_value ());
539
540 FloatNDArray x (args(2).float_array_value ());
541
542 if (! error_state)
543 {
544 FloatNDArray si;
545
546 if (nargin == 3 || args(3).is_empty ())
547 {
548 octave_idx_type a_len = a.length ();
549 octave_idx_type b_len = b.length ();
550
551 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
552
553 dim_vector si_dims = x.dims ();
554 for (int i = dim; i > 0; i--)
555 si_dims(i) = si_dims(i-1);
556 si_dims(0) = si_len;
557
558 si.resize (si_dims, 0.0);
559 }
560 else
561 {
562 dim_vector si_dims = args (3).dims ();
563 bool si_is_vector = true;
564 for (int i = 0; i < si_dims.length (); i++)
565 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
566 {
567 si_is_vector = false;
568 break;
569 }
570
571 si = args(3).float_array_value ();
572
573 if (si_is_vector)
574 si = si.reshape (dim_vector (si.numel (), 1));
575 }
576
577 if (! error_state)
578 {
579 FloatNDArray y (filter (b, a, x, si, dim));
580
581 if (nargout == 2)
582 retval(1) = si;
583
584 retval(0) = y;
585 }
586 else
587 error (errmsg);
588 }
589 else
590 error (errmsg);
591 }
592 else
593 {
594 ColumnVector b (args(0).vector_value ());
595 ColumnVector a (args(1).vector_value ());
596
597 NDArray x (args(2).array_value ());
598
599 if (! error_state)
600 {
601 NDArray si;
602
603 if (nargin == 3 || args(3).is_empty ())
604 {
605 octave_idx_type a_len = a.length ();
606 octave_idx_type b_len = b.length ();
607
608 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
609
610 dim_vector si_dims = x.dims ();
611 for (int i = dim; i > 0; i--)
612 si_dims(i) = si_dims(i-1);
613 si_dims(0) = si_len;
614
615 si.resize (si_dims, 0.0);
616 }
617 else
618 {
619 dim_vector si_dims = args (3).dims ();
620 bool si_is_vector = true;
621 for (int i = 0; i < si_dims.length (); i++)
622 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
623 {
624 si_is_vector = false;
625 break;
626 }
627
628 si = args(3).array_value ();
629
630 if (si_is_vector)
631 si = si.reshape (dim_vector (si.numel (), 1));
632 }
633
634 if (! error_state)
635 {
636 NDArray y (filter (b, a, x, si, dim));
637
638 if (nargout == 2)
639 retval(1) = si;
640
641 retval(0) = y;
642 }
643 else
644 error (errmsg);
645 }
646 else
647 error (errmsg);
648 }
649 }
650
651 return retval;
652}
653
654template MArrayN<double>
655filter (MArray<double>&, MArray<double>&, MArrayN<double>&,
656 MArrayN<double>&, int dim);
657
658template MArrayN<double>
659filter (MArray<double>&, MArray<double>&, MArrayN<double>&, int dim);
660
661template MArrayN<Complex>
662filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&,
663 MArrayN<Complex>&, int dim);
664
665template MArrayN<Complex>
666filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&, int dim);
667
668template MArrayN<float>
669filter (MArray<float>&, MArray<float>&, MArrayN<float>&,
670 MArrayN<float>&, int dim);
671
672template MArrayN<float>
673filter (MArray<float>&, MArray<float>&, MArrayN<float>&, int dim);
674
675template MArrayN<FloatComplex>
676filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&,
677 MArrayN<FloatComplex>&, int dim);
678
679template MArrayN<FloatComplex>
680filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&, int dim);
681
682/*
683%!shared a, b, x, r
684%!test
685%! a = [1 1];
686%! b = [1 1];
687%! x = zeros(1,10); x(1) = 1;
688%! assert(all(filter(b, [1], x ) == [1 1 0 0 0 0 0 0 0 0] ))
689%! assert(all(filter(b, [1], x.') == [1 1 0 0 0 0 0 0 0 0].'))
690%! assert(all(filter(b.', [1], x ) == [1 1 0 0 0 0 0 0 0 0] ))
691%! assert(all(filter(b.', [1], x.') == [1 1 0 0 0 0 0 0 0 0].'))
692%! assert(all(filter([1], a, x ) == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ))
693%! assert(all(filter([1], a, x.') == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'))
694%! assert(all(filter([1], a.', x ) == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ))
695%! assert(all(filter([1], a.', x.') == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'))
696%! assert(all(filter(b, a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
697%! assert(all(filter(b.', a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
698%! assert(all(filter(b, a.', x ) == [1 0 0 0 0 0 0 0 0 0] ))
699%! assert(all(filter(b.', a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
700%! assert(all(filter(b, a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
701%! assert(all(filter(b.', a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
702%! assert(all(filter(b, a.', x.') == [1 0 0 0 0 0 0 0 0 0].'))
703%! assert(all(filter(b.', a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
704%!
705%!test
706%! r = sqrt(1/2)*(1+i);
707%! a = a*r;
708%! b = b*r;
709%! assert(all(filter(b, [1], x ) == r*[1 1 0 0 0 0 0 0 0 0] ))
710%! assert(all(filter(b, [1], r*x ) == r*r*[1 1 0 0 0 0 0 0 0 0] ))
711%! assert(all(filter(b, [1], x.' ) == r*[1 1 0 0 0 0 0 0 0 0].' ))
712%! assert(all(filter(b, a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
713%! assert(all(filter(b, a, r*x ) == r*[1 0 0 0 0 0 0 0 0 0] ))
714%!
715%!shared a, b, x, y, so
716%!test
717%! a = [1,1]; b=[1,1];
718%! x = zeros(1,10); x(1) = 1;
719%! [y, so] = filter(b, [1], x, [-1]);
720%! assert(all(y == [0 1 0 0 0 0 0 0 0 0]))
721%! assert(so,0)
722%!
723%!test
724%! x = zeros(10,3); x(1,1)=-1; x(1,2)=1;
725%! y0 = zeros(10,3); y0(1:2,1)=-1; y0(1:2,2)=1;
726%! y = filter(b,[1],x);
727%! assert(all(all(y==y0)))
728%!
729%!test
730%! a = [1,1]; b=[1,1];
731%! x = zeros(4,4,2); x(1,1:4,1) = +1; x(1,1:4,2) = -1;
732%! y0 = zeros(4,4,2); y0(1:2,1:4,1) = +1; y0(1:2,1:4,2) = -1;
733%! y = filter(b, [1], x);
734%! assert(all(all(all(y==y0))))
735
736%% Should put some tests of the "DIM" parameter in here.
737
738 */
739
740/*
741;;; Local Variables: ***
742;;; mode: C++ ***
743;;; End: ***
744*/