b = fireqint(n,l,alpha)
designs an FIR equiripple filter useful for interpolating input signals.

b = fireqint(n,l,alpha,w)
allows you to specify a vector of weights in w.

b = fireqint('minorder', l,alpha,r)
allows you to design a minimum-order filter that meets the design specifications. When you
use the input argument 'minorder', you must provide the maximum ripple
vector r.

b = fireqint({'minorder',initord},l,alpha,r)
allows you to provide an initial estimate of the filter order in the input argument
initord. Again, you must provide r, the vector
of maximum deviation or ripples from the ideal filter magnitude response.

Design a minimum order interpolation filter with interpolation factor set to 6, and inverse measure of transition bandwidth set to 0.8. A vector of ripples must be supplied with the input argument, minorder.

Order of the equiripple filter, specified as a positive integer. Filter order must
be three or more.

Data Types: double

l — Interpolation factor positive integer

Interpolation factor, specified as a positive integer.

Data Types: double

alpha — Inverse measure of transition bandwidth positive scalar in the range (0,1)

Inverse measure of the transition bandwidth, specified as a positive scalar in the
range (0,1).

The alpha argument is inversely proportional to the transition
bandwidth of the filter. It also affects the bandwidth of the don't-care regions in the
stopband. Specifying alpha allows you to control how much of the
Nyquist interval your input signal occupies. This can be beneficial for signals to be
interpolated because it allows you to increase the transition bandwidth without
affecting the interpolation, resulting in better stopband attenuation for a given
l. If you set alpha argument to
1, then fireqint function assumes that your
signal occupies the entire Nyquist interval. Setting the alpha
argument to a value less than one allows for don't-care regions in the stopband. For
example, if your input occupies half the Nyquist interval, you could set the
alpha to 0.5.

The signal to be interpolated is assumed to have zero (or negligible) power in the
frequency band between (alpha*π) and π. The input argument,
alpha must therefore be a positive scalar between 0 and 1. The
fireqint function treats such bands as don't-care regions for
assessing filter design.

Data Types: double

w — Weights row vector of positive scalars

Weights applied to passband ripple and stopband attenuation, specified as a row
vector of positive scalars. The number of weights required in w is
given by 1 + floor(l/2). Using
weights enables you to specify different attenuations in different parts of the
stopband, as well as providing the ability to adjust the compromise between passband
ripple and stopband attenuation.

Data Types: double

r — Maximum deviation from ideal filter magnitude response vector

Maximum deviations or ripples from the ideal filter magnitude response, specified as
a vector. The number of elements required in r is given by 1 +
floor(l/2).

Data Types: double

initord — Initial filter order positive integer

Initial filter order when designing a minimum order filter that meets design
specifications, specified as a positive integer.

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