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Constrained-band equiripple FIR filter

`b = fircband(n,f,a,w,c)`

b = fircband(n,f,a,s)

b = fircband(...,'1')

b = fircband(...,'minphase')

b = fircband(..., 'check')

b = fircband(...,{lgrid})

[b,err] = fircband(...)

[b,err,res] = fircband(...)

`fircband`

is a minimax filter design algorithm
that you use to design the following types of real FIR filters:

Types 1-4 linear phase

Type 1 is even order, symmetric

Type 2 is odd order, symmetric

Type 3 is even order, antisymmetric

Type 4 is odd order, antisymmetric

Minimum phase

Maximum phase

Minimum order (even or odd), extra ripple

Maximal ripple

Constrained ripple

Single-point band (notching and peaking)

Forced gain

Arbitrary shape frequency response curve filters

`b = fircband(n,f,a,w,c)`

designs
filters having constrained error magnitudes (ripples). `c`

is
a cell array of character vectors of the same length as `w`

.
The entries of `c`

must be either '`c'`

to
indicate that the corresponding element in `w`

is
a constraint (the ripple for that band cannot exceed that value) or
'`w'`

indicating that the corresponding entry in `w`

is
a weight. There must be at least one unconstrained band — `c`

must
contain at least one ** w** entry. For instance,
the example 'Design a Constrained Lowpass Filter' uses a weight of
one in the passband, and constrains the stopband ripple not to exceed
0.2 (about 14 dB).

A hint about using constrained values: if your constrained filter does not touch the constraints, increase the error weighting you apply to the unconstrained bands.

Notice that, when you work with constrained stopbands, you enter
the stopband constraint according to the standard conversion formula
for power — the resulting filter attenuation or constraint
equals 20*log(*constraint*) where *constraint* is
the value you enter in the function. For example, to set 20 dB of
attenuation, use a value for the constraint equal to 0.1. This applies
to constrained stopbands only.

`b = fircband(n,f,a,s)`

is
used to design filters with special properties at certain frequency
points. `s`

is a cell array of character vectors
and must be the same length as `f`

and `a`

.
Entries of `s`

must be one of:

`'`

`n`

`'`

— normal frequency point.`'`

`s`

`'`

— single-point band. The frequency band is given by a single point. You must specify the corresponding gain at this frequency point in`a`

.`'`

`f`

`'`

— forced frequency point. Forces the gain at the specified frequency band to be the value specified.`'`

`i`

`'`

— indeterminate frequency point. Use this argument when bands abut one another (no transition region).

`b = fircband(...,'1')`

designs
a type 1 filter (even-order symmetric). You could also specify type
2 (odd-order symmetric), type 3 (even-order antisymmetric), or type
4 (odd-order antisymmetric) filters. Note there are restrictions on `a`

at `f`

=
0 or `f`

= 1 for types 2, 3, and 4.

`b = fircband(...,'minphase')`

designs
a minimum-phase FIR filter. There is also '** maxphase**'.

`b = fircband(..., 'check')`

produces
a warning when there are potential transition-region anomalies in
the filter response.

`b = fircband(...,{lgrid})`

,
where {`lgrid`

} is a scalar cell array containing
an integer, controls the density of the frequency grid.

`[b,err] = fircband(...)`

returns
the unweighted approximation error magnitudes. `err`

has
one element for each independent approximation error.

`[b,err,res] = fircband(...)`

returns
a structure `res`

of optional results computed by `fircband`

,
and contains the following fields:

Structure Field | Contents |
---|---|

`res.fgrid` | Vector containing the frequency grid used in the filter design optimization |

`res.des` | Desired response on |

`res.wt` | Weights on |

`res.h` | Actual frequency response on the frequency grid |

`res.error` | Error at each point (desired response - actual response) on the frequency grid |

`res.iextr` | Vector of indices into |

`res.fextr` | Vector of extremely frequencies |

`res.order` | Filter order |

`res.edgecheck` | Transition-region anomaly check. One element per band
edge. Element values have the following meanings: 1
= OK , 0 = probable transition-region
anomaly , -1 = edge not checked. Computed when you specify the |

`res.iterations` | Number of Remez iterations for the optimization |

`res.evals` | Number of function evaluations for the optimization |

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