One-dimensional digital filter of fi objects
y = filter(b,1,x)
[y,zf] = filter(b,1,x,zi)
y = filter(b,1,x,zi,dim)
y = filter(b,1,x) filters the data in the fixed-point vector x using the filter described by the fixed-point vector b. The function returns the filtered data in the output fi object y. Inputs b and x must be fi objects. filter always operates along the first non-singleton dimension. Thus, the filter operates along the first dimension for column vectors and nontrivial matrices, and along the second dimension for row vectors.
[y,zf] = filter(b,1,x,zi) gives access to initial and final conditions of the delays, zi, and zf. zi is a vector of length length(b)-1, or an array with the leading dimension of size length(b)-1 and with remaining dimensions matching those of x. zi must be a fi object with the same data type as y and zf. If you do not specify a value for zi, it defaults to a fixed-point array with a value of 0 and the appropriate numerictype and size.
y = filter(b,1,x,zi,dim) performs the filtering operation along the specified dimension. If you do not want to specify the vector of initial conditions, use  for the input argument zi.
Fixed-point vector of the filter coefficients.
Fixed-point vector containing the data for the function to filter.
Fixed-point vector containing the initial conditions of the delays. If the initial conditions of the delays are zero, you can specify zero, or, if you do not know the appropriate size and numerictype for zi, use .
If you do not specify a value for zi, the parameter defaults to a fixed-point vector with a value of zero and the same numerictype and size as the output zf (default).
Dimension along which to perform the filtering operation.
Output vector containing the filtered fixed-point data.
Fixed-point output vector containing the final conditions of the delays.
The following example filters a high-frequency fixed-point sinusoid from a signal that contains both a low- and high-frequency fixed-point sinusoid.
w1 = .1*pi; w2 = .6*pi; n = 0:999; xd = sin(w1*n) + sin(w2*n); x = sfi(xd,12); b = ufi([.1:.1:1,1-.1:-.1:.1]/4,10); gd = (length(b)-1)/2; y = filter(b,1,x); % Plot results, accommodate for group-delay of filter plot(n(1:end-gd),x(1:end-gd)) hold on plot(n(1:end-gd),y(gd+1:end),'r--') axis([0 50 -2 2]) legend('Unfiltered signal','Filtered signal') xlabel('Sample index (n)') ylabel('Signal value')
The resulting plot shows both the unfiltered and filtered signals.
The filter length is length(b), or the number of filter coefficients specified in the fixed-point vector b.
The filter order is the number of states (delays) of the filter, and is equal to L-1.
The filter function only supports FIR filters. In the general filter representation, b/a, the denominator, a, of an FIR filter is the scalar 1, which is the second input of this function.
The numerictype of b can be different than the numerictype of x.
If you want to specify initial conditions, but do not know what numerictype to use, first try filtering your data without initial conditions. You can do so by specifying  for the input zi. After performing the filtering operation, you have the numerictype of y and zf (if requested). Because the numerictype of zi must match that of y and zf, you now know the numerictype to use for the initial conditions.
The filter function uses a Direct-Form Transposed FIR implementation of the following difference equation:
The following diagram shows the direct-form transposed FIR filter structure used by the filter function:
The filter function uses the following rules regarding fimath behavior:
globalfimath is obeyed.
If any of the inputs has an attached fimath, then it is used for intermediate calculations.
If more than one input has an attached fimath, then the fimaths must be equal.
The output, y, is always associated with the default fimath.
If the input vector, zi, has an attached fimath, then the output vector, zf, retains this fimath.