# fir2: FIR filter generation In signal: Signal Processing

## Description

FIR filter coefficients for a filter with the given order and frequency cutoffs.

## Usage

 `1` ```fir2(n, f, m, grid_n = 512, ramp_n = grid_n/20, window = hamming(n + 1)) ```

## Arguments

 `n` order of the filter (1 less than the length of the filter) `f` band edges, strictly increasing vector in the range [0, 1] where 1 is the Nyquist frequency. The first element must be 0 and the last element must be 1. If elements are identical, it indicates a jump in frequency response. `m` magnitude at band edges, a vector of `length(f)`. `grid_n` length of ideal frequency response function defaults to 512, should be a power of 2 bigger than `n`. `ramp_n` transition width for jumps in filter response defaults to `grid_n/20`. A wider ramp gives wider transitions but has better stopband characteristics. `window` smoothing window. The returned filter is the same shape as the smoothing window.

## Value

The FIR filter coefficients, an array of `length(n+1)`, of class `Ma`.

## Author(s)

Original Octave version by Paul Kienzle, pkienzle@user.sf.net. Conversion to R by Tom Short.

## References

Octave Forge https://octave.sourceforge.io/

`filter`, `Ma`, `fftfilt`, `fir1`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```f <- c(0, 0.3, 0.3, 0.6, 0.6, 1) m <- c(0, 0, 1, 1/2, 0, 0) fh <- freqz(fir2(100, f, m)) op <- par(mfrow = c(1, 2)) plot(f, m, type = "b", ylab = "magnitude", xlab = "Frequency") lines(fh\$f / pi, abs(fh\$h), col = "blue") # plot in dB: plot(f, 20*log10(m+1e-5), type = "b", ylab = "dB", xlab = "Frequency") lines(fh\$f / pi, 20*log10(abs(fh\$h)), col = "blue") par(op) ```

### Example output

```Attaching package: 'signal'

The following objects are masked from 'package:stats':

filter, poly
```

signal documentation built on May 25, 2021, 9:06 a.m.