resample {gsignal}

Change sampling rate

Description

Resample using a polyphase algorithm.

Usage

resample(x, p, q, h)

Arguments

x

input data, specified as a numeric vector or matrix. In case of a vector it represents a single signal; in case of a matrix each column is a signal.

p, q

resampling factors, specified as positive integers. p / q is the resampling factor.

h

Impulse response of the FIR filter specified as a numeric vector or matrix. If it is a vector, then it represents one FIR filter to may be applied to multiple signals in x; if it is a matrix, then each column is a separate FIR impulse response. If not specified, a FIR filter based on a Kaiser window is designed.

Details

If h is not specified, this function will design an optimal FIR filter using a Kaiser-Bessel window. The filter length and the parameter \beta are computed based on ref [2], Chapter 7, Eq. 7.63 (p. 476), and Eq. 7.62 (p. 474), respectively.

Value

output signal, returned as a vector or matrix. Each column has length ceiling(((length(x) - 1) * p + length(h)) / q)..

Author(s)

Eric Chassande-Mottin, [e-mail].
Conversion to R by Geert van Boxtel, [e-mail].

References

[1] Proakis, J.G., and Manolakis, D.G. (2007). Digital Signal Processing: Principles, Algorithms, and Applications, 4th ed., Prentice Hall, Chap. 6.
[2] Oppenheim, A.V., Schafer, R.W., and Buck, J.R. (1999). Discrete-time signal processing, Signal processing series, Prentice-Hall.

See Also

kaiser

Examples

lx <- 60
tx <- seq(0, 360, length.out = lx)
x <- sin(2 * pi * tx / 120)

# upsample
p <- 3; q <- 2
ty <- seq(0, 360, length.out = lx * p / q)
y <- resample(x, p, q)

# downsample
p <- 2; q <- 3
tz <- seq(0, 360, length.out = lx * p / q)
z <- resample(x, p, q)

# plot
plot(tx, x, type = "b", col = 1, pch = 1,
 xlab = "", ylab = "")
points(ty, y, col = 2, pch = 2)
points(tz, z, col = 3, pch = 3)
legend("bottomleft", legend = c("original", "upsampled", "downsampled"),
  lty = 1, pch = 1:3, col = 1:3)