Company Events Academic Community Support Solutions Products & Services Contact NI MyNI

tf_estimateplot (MathScript RT Module Function)

LabVIEW 2012 MathScript RT Module Help

Edition Date: June 2012

Part Number: 373123C-01

»View Product Info
Download Help (Windows Only)

Owning Class: spectral analysis

Requires: MathScript RT Module

Syntax

tf_estimateplot(x, y)

tf_estimateplot(x, y, win)

tf_estimateplot(x, y, win, noverlap)

tf_estimateplot(x, y, win, noverlap, fftsize)

tf_estimateplot(x, y, win, noverlap, range)

tf_estimateplot(x, y, win, noverlap, fftsize, fs)

tf_estimateplot(x, y, win, noverlap, fftsize, range)

tf_estimateplot(x, y, win, noverlap, fftsize, fs, range)

Txy = tf_estimateplot(x, y)

Txy = tf_estimateplot(x, y, win)

Txy = tf_estimateplot(x, y, win, noverlap)

Txy = tf_estimateplot(x, y, win, noverlap, fftsize)

Txy = tf_estimateplot(x, y, win, noverlap, range)

Txy = tf_estimateplot(x, y, win, noverlap, fftsize, fs)

Txy = tf_estimateplot(x, y, win, noverlap, fftsize, range)

Txy = tf_estimateplot(x, y, win, noverlap, fftsize, fs, range)

[Txy, w] = tf_estimateplot(x, y)

[Txy, w] = tf_estimateplot(x, y, win)

[Txy, w] = tf_estimateplot(x, y, win, noverlap)

[Txy, w] = tf_estimateplot(x, y, win, noverlap, fftsize)

[Txy, w] = tf_estimateplot(x, y, win, noverlap, range)

[Txy, w] = tf_estimateplot(x, y, win, noverlap, fftsize, range)

[Txy, f] = tf_estimateplot(x, y, win, noverlap, fftsize, fs)

[Txy, f] = tf_estimateplot(x, y, win, noverlap, fftsize, fs, range)

Legacy Name: tfestimate

Description

Estimates a transfer function between the input signal and the output signal. If you do not request an output, this function plots the estimate of the transfer function in the current plot window.

Details

Examples

Inputs

Name Description
x Specifies the input signal. x is a real or complex vector.
y Specifies the output signal. y is a real or complex vector. length(x) must equal length(y).
win Specifies the window to apply to each segment of x and y. The length of win determines the number of segments into which LabVIEW divides x and y. win can be a vector that represents the window coefficients or an integer that represents a Hamming window with a length of win. The default is a Hamming window where LabVIEW divides x and y into eight sections.
noverlap Specifies the number of data elements that overlap between adjacent segments of data. noverlap must be less than the length of win. The default is the length that results in an overlap of half of the data elements between adjacent segments.
fftsize Specifies the length of the FFT to perform on each segment of the data. The default is the next power of 2 greater than the length of each segment of x and y if this number is greater than 256. Otherwise, the default is 256.
fs Specifies the sampling frequency of the input sequences in Hz. If you specify fs, LabVIEW returns the output frequencies in Hz. Otherwise, LabVIEW returns the output frequencies in radians per sample.
range Specifies the range of the estimate of the transfer function. range is a string that accepts the following values.

'onesided' (default) LabVIEW returns the single-sided estimated transfer function.
'twosided' LabVIEW returns the double-sided estimated transfer function.

Outputs

Name Description
Txy Returns the estimate of the transfer function of x and y. If both x and y are real and range is 'onesided', the length of Txy is fftsize / 2 + 1 for an even fftsize and (fftsize + 1) / 2 for an odd fftsize. Otherwise, the length of Txy is fftsize.
w Returns the frequencies in radians per sample at the points where LabVIEW evaluates Txy.
f Returns the frequencies in Hz at the points where LabVIEW evaluates Txy.

Details

This function uses the Welch method to calculate the power spectrum of x and the cross power spectrum of x and y. LabVIEW uses the following equation to calculate the estimate of the transfer function:

Txy(f) = P_xy(f) / P_xx(f)

The following table lists the support characteristics of this function.

Supported in the LabVIEW Run-Time Engine Yes (if you request output)
Supported on RT targets Yes (if you request output)
Suitable for bounded execution times on RT Not characterized

Examples

fs = 1000;
t = 0:1/fs:0.2;
fftsize = 1024;
window = win_hann2(64);
noverlap = 32;
noise = randnormal(size(t));
x = sin(2*pi*100*t) + cos(2*pi*250*t) + noise;
y = 2*sin(2*pi*50*t) + 3*cos(2*pi*400*t) - noise;
Txy = tf_estimateplot(x, y, window, noverlap, fftsize, fs);

Related Topics

coherence_ms
crosspsd
psd_welch
spectrogram
tf_estimate


 

Your Feedback! poor Poor  |  Excellent excellent   Yes No
 Document Quality? 
 Answered Your Question? 
Add Comments 1 2 3 4 5 submit