# stft

Short-time Fourier transform

## Syntax

## Description

returns the
Short-Time Fourier Transform (STFT) of
`s`

= stft(`x`

)`x`

.

specifies additional options using name-value pair arguments. Options include the FFT
window and length. These arguments can be added to any of the previous input
syntaxes.`s`

= stft(___,`Name,Value`

)

`stft(___)`

with no output arguments plots the
magnitude of the STFT in the current figure window.

## Examples

### 3D STFT Visualization

Generate two seconds of a voltage controlled oscillator output, controlled by a sinusoid sampled at 10 kHz.

fs = 10e3; t = 0:1/fs:2; x = vco(sin(2*pi*t),[0.1 0.4]*fs,fs);

Compute and plot the STFT of the signal. Use a Kaiser window of length 256 and shape parameter $\beta =5$. Specify the length of overlap as 220 samples and DFT length as 512 points. Plot the STFT with default colormap and view.

stft(x,fs,'Window',kaiser(256,5),'OverlapLength',220,'FFTLength',512);

Change the view to display the STFT as a waterfall plot. Set the colormap to `jet`

.

```
view(-45,65)
colormap jet
```

### STFT of Quadratic Chirp

Generate a quadratic chirp sampled at 1 kHz for 2 seconds. The instantaneous frequency is 100 Hz at $\mathit{t}=0$ and crosses 200 Hz at $\mathit{t}=1$ second.

ts = 0:1/1e3:2; f0 = 100; f1 = 200; x = chirp(ts,f0,1,f1,'quadratic',[],'concave');

Compute and display the STFT of the quadratic chirp with a duration of 1 ms.

d = seconds(1e-3); win = hamming(100,'periodic'); stft(x,d,'Window',win,'OverlapLength',98,'FFTLength',128);

### STFT Frequency Ranges

Generate a signal sampled at 5 kHz for 4 seconds. The signal consists of a set of pulses of decreasing duration separated by regions of oscillating amplitude and fluctuating frequency with an increasing trend. Plot the signal.

fs = 5000; t = 0:1/fs:4-1/fs; x = besselj(0,600*(sin(2*pi*(t+1).^3/30).^5)); plot(t,x)

Compute the one-sided, two-sided, and centered short-time Fourier transforms of the signal. In all cases, use a 202-sample Kaiser window with shape factor $\beta =10$ to window the signal segments. Display the frequency range used to compute each transform.

rngs = ["onesided" "twosided" "centered"]; for kj = 1:length(rngs) opts = {'Window',kaiser(202,10),'FrequencyRange',rngs(kj)}; [~,f] = stft(x,fs,opts{:}); subplot(length(rngs),1,kj) stft(x,fs,opts{:}) title(sprintf('''%s'': [%5.3f, %5.3f] kHz',rngs(kj),[f(1) f(end)]/1000)) end

Repeat the computation, but now change the length of the Kaiser window to 203, an odd number. The `'twosided'`

frequency interval does not change. The other two frequency intervals become open at the higher end.

for kj = 1:length(rngs) opts = {'Window',kaiser(203,10),'FrequencyRange',rngs(kj)}; [~,f] = stft(x,fs,opts{:}); subplot(length(rngs),1,kj) stft(x,fs,opts{:}) title(sprintf('''%s'': [%5.3f, %5.3f] kHz',rngs(kj),[f(1) f(end)]/1000)) end

### STFT of Multichannel Signals

Generate a three-channel signal consisting of three different chirps sampled at 1 kHz for one second.

The first channel consists of a concave quadratic chirp with instantaneous frequency 100 Hz at

*t =*0 and crosses 300 Hz at*t =*1 second. It has an initial phase equal to 45 degrees.The second channel consists of a convex quadratic chirp with instantaneous frequency 100 Hz at

*t =*0 and crosses 500 Hz at*t =*1 second.The third channel consists of a logarithmic chirp with instantaneous frequency 300 Hz at

*t =*0 and crosses 500 Hz at*t =*1 second.

Compute the STFT of the multichannel signal using a periodic Hamming window of length 128 and an overlap length of 50 samples.

fs = 1e3; t = 0:1/fs:1-1/fs; x = [chirp(t,100,1,300,'quadratic',45,'concave'); chirp(t,100,1,500,'quadratic',[],'convex'); chirp(t,300,1,500,'logarithmic')]'; [S,F,T] = stft(x,fs,'Window',hamming(128,'periodic'),'OverlapLength',50);

Visualize the STFT of each channel as a waterfall plot. Control the behavior of the axes using the helper function `helperGraphicsOpt`

.

waterfall(F,T,abs(S(:,:,1))') helperGraphicsOpt(1)

waterfall(F,T,abs(S(:,:,2))') helperGraphicsOpt(2)

waterfall(F,T,abs(S(:,:,3))') helperGraphicsOpt(3)

This helper function sets the appearance and behavior of the current axes.

function helperGraphicsOpt(ChannelId) ax = gca; ax.XDir = 'reverse'; ax.ZLim = [0 30]; ax.Title.String = ['Input Channel: ' num2str(ChannelId)]; ax.XLabel.String = 'Frequency (Hz)'; ax.YLabel.String = 'Time (seconds)'; ax.View = [30 45]; end

## Input Arguments

`x`

— Input signal

vector | matrix | timetable

Input signal, specified as a vector, a matrix, or a MATLAB^{®}
`timetable`

.

**Note**

If you invert `s`

using `istft`

and want the result to be the same length as `x`

, the value of
`(length(x)-noverlap)/(length(window)-noverlap)`

must be an
integer.

If the input has multiple channels, specify

`x`

as a matrix where each column corresponds to a channel.For timetable input,

`x`

must contain uniformly increasing finite row times. If a timetable has missing or duplicate time points, you can fix it using the tips in Clean Timetable with Missing, Duplicate, or Nonuniform Times.For multichannel timetable input, specify

`x`

as a timetable with a single variable containing a matrix or a timetable with multiple variables each containing a column vector. All variables must have the same precision.

Each channel of `x`

must have a length greater than or
equal to the window length.

**Example: **`chirp(0:1/4e3:2,250,1,500,'quadratic')`

specifies a
single-channel chirp.

**Example: **`timetable(rand(5,2),'SampleRate',1)`

specifies a
two-channel random variable sampled at 1 Hz for 4 seconds.

**Example: **`timetable(rand(5,1),rand(5,1),'SampleRate',1)`

specifies a
two-channel random variable sampled at 1 Hz for 4 seconds.

**Data Types: **`double`

| `single`

**Complex Number Support: **Yes

`fs`

— Sample rate

`2`*π*

(default) | positive scalar

*π*

Sample rate, specified as a positive scalar. This argument applies only when
`x`

is a vector or a matrix.

**Data Types: **`double`

| `single`

### Name-Value Arguments

Specify optional
comma-separated pairs of `Name,Value`

arguments. `Name`

is
the argument name and `Value`

is the corresponding value.
`Name`

must appear inside quotes. You can specify several name and value
pair arguments in any order as
`Name1,Value1,...,NameN,ValueN`

.

**Example:**

`'Window',hamming(100),'OverlapLength',50,'FFTLength',128`

windows the data using a 100-sample Hamming window, with 50 samples of overlap between
adjoining segments and a 128-point FFT.`Window`

— Spectral window

`hann(128,'periodic')`

(default) | vector

Spectral window, specified as a vector. If you do not specify the window or
specify it as empty, the function uses a Hann window of length 128. The length of
`'Window'`

must be greater than or equal to 2.

For a list of available windows, see Windows.

**Example: **`hann(N+1)`

and
`(1-cos(2*pi*(0:N)'/N))/2`

both specify a Hann window of length
`N`

+ 1.

**Data Types: **`double`

| `single`

`OverlapLength`

— Number of overlapped samples

`75%`

of window length (default) | nonnegative integer

Number of overlapped samples, specified as a positive integer smaller than the
length of `'Window'`

. If you omit
`'OverlapLength'`

or specify it as empty, it is set to the
largest integer less than 75% of the window length, which is 96 samples for the
default Hann window.

**Data Types: **`double`

| `single`

`FFTLength`

— Number of DFT points

`128`

(default) | positive integer

Number of DFT points, specified as a positive integer. The value must be greater than or equal to the window length. If the length of the input signal is less than the DFT length, the data is padded with zeros.

**Data Types: **`double`

| `single`

`FrequencyRange`

— STFT frequency range

`'centered'`

(default) | `'twosided'`

| `'onesided'`

STFT frequency range, specified as `'centered'`

,
`'twosided'`

, or `'onesided'`

.

`'centered'`

— Compute a two-sided, centered STFT. If`'FFTLength'`

is even, then`s`

is computed over the interval (–*π*,*π*] rad/sample. If`'FFTLength'`

is odd, then`s`

is computed over the interval (–*π*,*π*) rad/sample. If you specify time information, then the intervals are (–*f*_{s},*f*_{s}/2] cycles/unit time and (–*f*_{s},*f*_{s}/2) cycles/unit time, respectively, where*f*_{s}is the effective sample rate.`'twosided'`

— Compute a two-sided STFT over the interval [0, 2*π*) rad/sample. If you specify time information, then the interval is [0,*f*_{s}) cycles/unit time.`'onesided'`

— Compute a one-sided STFT. If`'FFTLength'`

is even, then`s`

is computed over the interval [0,*π*] rad/sample. If`'FFTLength'`

is odd, then`s`

is computed over the interval [0,*π*) rad/sample. If you specify time information, then the intervals are [0,*f*_{s}/2] cycles/unit time and [0,*f*_{s}/2) cycles/unit time, respectively, where*f*_{s}is the effective sample rate. This option is valid only for real signals.**Note**When this argument is set to

`'onesided'`

,`stft`

outputs the values in the positive Nyquist range and does not conserve the total power.

For an example, see STFT Frequency Ranges.

**Data Types: **`char`

| `string`

`OutputTimeDimension`

— Output time dimension

`'acrosscolumns'`

(default) | `'downrows'`

Output time dimension, specified as `'acrosscolumns'`

or
`'downrows'`

. Set this value to `'downrows'`

if
you want the time dimension of `s`

down the rows and the frequency
dimension across the columns. Set this value to `'acrosscolumns'`

if
you want the time dimension of `s`

across the columns and the
frequency dimension down the rows. This input is ignored if the function is called
without output arguments.

## Output Arguments

`s`

— Short-time Fourier transform

matrix | 3-D array

Short-time Fourier transform, returned as a matrix or a 3-D array. Time increases
across the columns of `s`

and frequency increases down the rows. The
third dimension, if present, corresponds to the input channels.

If the signal

`x`

has*N*time samples, then_{x}`s`

has*k*columns, where*k*= ⌊(*N*–_{x}*L*)/(*M*–*L*)⌋,*M*is the length of`'Window'`

,*L*is the`'OverlapLength'`

, and the ⌊ ⌋ symbols denote the floor function.The number of rows in

`s`

is equal to the value specified in`'FFTLength'`

.

**Data Types: **`double`

| `single`

`f`

— Frequencies

vector

Frequencies at which the STFT is evaluated, returned as a vector.

**Data Types: **`double`

| `single`

`t`

— Time instants

vector

Time instants, returned as a vector. `t`

contains the time values
corresponding to the centers of the data segments used to compute short-time power
spectrum estimates.

**Data Types: **`double`

| `single`

## More About

### Short-Time Fourier Transform

The short-time Fourier transform (STFT) is used to analyze how the frequency content of a nonstationary signal changes over time.

The STFT of a signal is calculated by sliding an *analysis window* of
length $$M$$ over the signal and calculating the discrete Fourier transform of the
windowed data. The window hops over the original signal at intervals of $$R$$ samples. Most window functions taper off at the edges to avoid spectral
ringing. If a nonzero overlap length $$L$$ is specified, overlap-adding the windowed segments compensates for the
signal attenuation at the window edges. The DFT of each windowed segment is added to a
matrix that contains the magnitude and phase for each point in time and frequency. The
number of columns in the STFT matrix is given by

$$k=\lfloor \frac{{N}_{x}-L}{M-L}\rfloor ,$$

where $${N}_{x}$$ is the length of the original signal $$x(n)$$ and the ⌊⌋ symbols denote the floor function. The number of rows in the matrix equals *N*_{DFT}, the number of DFT points, for centered and two-sided transforms and ⌊*N*_{DFT}/2⌋ + 1 for one-sided transforms.

The STFT matrix is given by $$X(f)=\left[\begin{array}{ccccc}{X}_{1}(f)& {X}_{2}(f)& {X}_{3}(f)& \cdots & {X}_{k}(f)\end{array}\right]$$ such that the $$m$$th element of this matrix is

$${X}_{m}(f)={\displaystyle \sum _{n=-\infty}^{\infty}x(n)g(n-mR){e}^{-j2\pi fn}},$$

where

$$g(n)$$ — Window function of length $$M$$.

$${X}_{m}(f)$$ — DFT of windowed data centered about time $$mR$$.

$$R$$ — Hop size between successive DFTs. The hop size is the difference between the window length $$M$$and the overlap length $$L$$.

The magnitude squared of the STFT yields the `spectrogram`

representation of the power spectral density of the function.

### Perfect Reconstruction

In general, computing the STFT of an input signal and inverting it does not result in perfect reconstruction. If you want the output of ISTFT to match the original input signal as closely as possible, the signal and the window must satisfy the following conditions:

Input size — If you invert the output of

`stft`

using`istft`

and want the result to be the same length as the input signal`x`

, the value of $$k\text{}=\text{}{\scriptscriptstyle \frac{(length(x)-noverlap)}{(length(window)-noverlap)}}$$ must be an integer.COLA compliance — Use COLA-compliant windows, assuming that you have not modified the short-time Fourier transform of the signal.

Padding — If the length of the input signal is such that the value of

*k*is not an integer, zero-pad the signal before computing the short-time Fourier transform. Remove the extra zeros after inverting the signal.

## References

[1] Mitra, Sanjit K.
*Digital Signal Processing: A Computer-Based Approach*. 2nd Ed. New
York: McGraw-Hill, 2001.

[2] Sharpe, Bruce.
*Invertibility of Overlap-Add Processing*. https://gauss256.github.io/blog/cola.html, accessed July 2019.

[3] Smith, Julius Orion.
*Spectral Audio Signal Processing*. https://ccrma.stanford.edu/~jos/sasp/, online book, 2011 edition, accessed
Nov 2018.

## Extended Capabilities

### Tall Arrays

Calculate with arrays that have more rows than fit in memory.

Usage notes and limitations:

`'OutputTimeDimension'`

must always be specified and set to
`'downrows'`

.

For more information, see Tall Arrays.

### C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

Timetables are not supported for code generation.

### GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

Timetables are not supported for code generation.

### Thread-Based Environment

Run code in the background using MATLAB® `backgroundPool`

or accelerate code with Parallel Computing Toolbox™ `ThreadPool`

.

Usage notes and limitations:

The syntax with no output arguments is not supported.

For more information, see Run MATLAB Functions in Thread-Based Environment.

### GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

**Introduced in R2019a**

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