This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English version of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materials including this page, select Japan from the country navigator on the bottom of this page.

dsp.IFFT System object

Inverse discrete Fourier transform (IDFFT)


The IFFT object computes the inverse discrete Fourier transform (IDFFT) of the input. The object uses one or more of the following fast Fourier transform (FFT) algorithms depending on the complexity of the input and whether the output is in linear or bit-reversed order:

  • Double-signal algorithm

  • Half-length algorithm

  • Radix-2 decimation-in-time (DIT) algorithm

  • Radix-2 decimation-in-frequency (DIF) algorithm

  • An algorithm chosen by FFTW [1], [2]

To compute the IFFT of the input:

  1. Define and set up your IFFT object. See Construction.

  2. Call step to compute the IFFT of the input according to the properties of dsp.IFFT. The behavior of step is specific to each object in the toolbox.


Starting in R2016b, instead of using the step method to perform the operation defined by the System object™, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.


ift = dsp.IFFT returns an IFFT object, ift, that computes the IDFT of a column vector or N-D array. For column vectors or N-D arrays, the IFFT object computes the IDFT along the first dimension of the array. If the input is a row vector, the IFFT object computes a row of single-sample IDFTs and issues a warning.

ift = dsp.IFFT('PropertyName',PropertyValue, ...) returns an IFFT object, ift, with each property set to the specified value.



FFT implementation

Specify the implementation used for the FFT as one of Auto | Radix-2 | FFTW. When you set this property to Radix-2, the FFT length must be a power of two.


Enable bit-reversed order interpretation of input elements

Set this property totrue if the order of Fourier transformed input elements to the IFFT object are in bit-reversed order. This property applies only when the FFTLengthSource property is Auto. The default is false, which denotes linear ordering.


Enable conjugate symmetric interpretation of input

Set this property to true if the input is conjugate symmetric to yield real-valued outputs. The discrete Fourier transform of a real valued sequence is conjugate symmetric, and setting this property to true optimizes the IDFT computation method. Setting this property to false for conjugate symmetric inputs may result in complex output values with nonzero imaginary parts. This occurs due to rounding errors. Setting this property to true for nonconjugate symmetric inputs results in invalid outputs. This property applies only when the FFTLengthSource property is Auto. The default is false.


Enable dividing output by FFT length

Specify whether to divide the IFFT output by the FFT length. The default is true and each element of the output is divided by the FFT length.


Source of FFT length

Specify how to determine the FFT length as Auto or Property. When you set this property to Auto, the FFT length equals the number of rows of the input signal. This property applies only when both the BitReversedInput and ConjugateSymmetricInput properties are false. The default is Auto.


FFT length

Specify the FFT length as a numeric scalar. This property applies when you set the BitReversedInput and ConjugateSymmetricInput properties to false, and the FFTLengthSource property to Property. The default is 64.

This property must be a power of two when the input is a fixed-point data type, or when you set the FFTImplementation property to Radix-2.

When you set the FFT implementation property to Radix-2, or when you set the BitReversedOutput property to true, this value must be a power of two.


Boolean value of wrapping or truncating input

Wrap input data when FFTLength is shorter than input length. If this property is set to true, modulo-length data wrapping occurs before the FFT operation, given FFTLength is shorter than the input length. If this property is set to false, truncation of the input data to the FFTLength occurs before the FFT operation. The default is true.

 Fixed-Point Properties


stepInverse discrete Fourier transform of input
Common to All System Objects

Create System object with same property values


Expected number of inputs to a System object


Expected number of outputs of a System object


Check locked states of a System object (logical)


Allow System object property value changes


expand all

Compute the FFT of a noisy sinusoidal input signal. The energy of the signal is stored as the magnitude square of the FFT coefficients. Determine the FFT coefficients which occupy 99.99% of the signal energy and reconstruct the time-domain signal by taking the IFFT of these coefficients. Compare the reconstructed signal with the original signal.

Note: If you are using R2016a or an earlier release, replace each call to the object with the equivalent step syntax. For example, obj(x) becomes step(obj(x).

Consider a time-domain signal , which is defined over the finite time interval . The energy of the signal is given by the following equation:

FFT Coefficients, are considered as signal values in the frequency domain. The energy of the signal in the frequency-domain is hence the sum of the squares of the magnitude of the FFT coefficients:

According to Parseval's theorem, the total energy of the signal in time or frequency-domain is the same.


Initialize a dsp.SineWave System object to generate a sine wave sampled at 44.1 kHz and has a frequency of 1000 Hz. Construct a dsp.FFT and dsp.IFFT objects to compute the FFT and the IFFT of the input signal.

The 'FFTLengthSource' property of each of these transform objects is set to 'Auto'. The FFT length is hence considered as the input frame size. The input frame size in this example is 1020, which is not a power of 2. Hence, select the 'FFTImplementation' as 'FFTW'.

L = 1020;
Sineobject = dsp.SineWave('SamplesPerFrame',L,'PhaseOffset',10,...
ft = dsp.FFT('FFTImplementation','FFTW');
ift = dsp.IFFT('FFTImplementation','FFTW','ConjugateSymmetricInput',true);


Stream in the noisy input signal. Compute the FFT of each frame and determine the coefficients which constitute 99.99% energy of the signal. Take IFFT of these coefficients to reconstruct the time-domain signal.

numIter = 1000;
for Iter = 1:numIter
    Sinewave1 = Sineobject();
    Input = Sinewave1 + 0.01*randn(size(Sinewave1));
    FFTCoeff = ft(Input);
    FFTCoeffMagSq = abs(FFTCoeff).^2;
    EnergyFreqDomain = (1/L)*sum(FFTCoeffMagSq);
    [FFTCoeffSorted, ind] = sort(((1/L)*FFTCoeffMagSq),1,'descend');
    CumFFTCoeffs = cumsum(FFTCoeffSorted);
    EnergyPercent = (CumFFTCoeffs/EnergyFreqDomain)*100;
    Vec = find(EnergyPercent > 99.99);
    FFTCoeffsModified = zeros(L,1);
    FFTCoeffsModified(ind(1:Vec(1))) = FFTCoeff(ind(1:Vec(1)));
    ReconstrSignal = ift(FFTCoeffsModified);

99.99% of the signal energy can be represented by the number of FFT coefficients given by Vec(1):

ans = 296

The signal is reconstructed efficiently using these coefficients. If you compare the last frame of the reconstructed signal with the original time-domain signal, you can see that the difference is very small and the plots match closely.

ans = 0.0431
hold on;
hold off;


This object implements the algorithm, inputs, and outputs described on the IFFT block reference page. The object properties correspond to the block parameters, except:

Output sampling mode parameter is not supported by dsp.IFFT.


[2] Frigo, M. and S. G. Johnson, “FFTW: An Adaptive Software Architecture for the FFT,”Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Vol. 3, 1998, pp. 1381-1384.

Extended Capabilities

See Also

System Objects

Introduced in R2012a

Was this topic helpful?