You are here : matlabSignal Processingpulstran

pulstran() - Signal Processing

pulstran generates pulse
trains from continuous functions or sampled prototype pulses.y = pulstran(t,d,'func') generates
a pulse train based on samples of a continuous function, 'func',
where 'func' is'gauspuls', for generating a Gaussian-modulated
sinusoidal pulse'rectpuls', for generating a sampled
aperiodic rectangle 'tripuls', for generating a sampled
aperiodic triangle pulstran is evaluated length(d) times
and returns the sum of the evaluations y = func(t-d(1)) + func(t-d(2)) + ... The function is evaluated over the range of argument values
specified in array t, after removing
a scalar argument offset taken from the vector d.
Note that func must be a vectorized function
that can take an array t as an argument.An optional gain factor may be applied to each delayed evaluation
by specifying d as a two-column matrix, with the
offset defined in column 1 and associated gain in
column 2 of d. Note that a row vector will be interpreted
as specifying delays only.pulstran(t,d,'func',p1,p2,...) allows
additional parameters to be passed to 'func' as
necessary. For example:func(t-d(1),p1,p2,...) + func(t-d(2),p1,p2,...) + ...
pulstran(t,d,p,fs) generates
a pulse train that is the sum of multiple delayed interpolations of
the prototype pulse in vector p, sampled at the
rate fs, where p spans
the time interval [0,(length(p)-1)/fs], and its
samples are identically 0 outside this interval.
By default, linear interpolation is used for generating delays.pulstran(t,d,p) assumes
that the sampling rate fs is equal to 1 Hz.pulstran(...,'func') specifies
alternative interpolation methods. See interp1 for
a list of available methods.


pulstrany = pulstran(t,d,'func')pulstran(t,d,'func',p1,p2,...)pulstran(t,d,p,fs)pulstran(t,d,p)pulstran(...,'func')


func(t-d(1),p1,p2,...) + func(t-d(2),p1,p2,...) + ...

Output / Return Value


Alternatives / See Also