Signal Processing Toolbox |

**Syntax**

Hmss = dspdata.msspectrum(Data) Hmss = dspdata.msspectrum(Data,Frequencies) Hmss = dspdata.msspectrum(...,'Fs',Fs) Hmss = dspdata.msspectrum(...,'SpectrumType',SpectrumType) Hmss

**=**dspdata.msspectrum(...,'CenterDC',flag)

**Description**

The mean-squared spectrum (MSS) is intended for discrete spectra. Unlike the power spectral density (PSD), the peaks in the MSS reflect the power in the signal at a given frequency. The MSS of a signal is the Fourier transform of that signal's autocorrelation.

```
Hmss = dspdata.msspectrum(Data)
```

uses the mean-square (power) spectrum data contained in `Data`

, which can be in the form of a vector or a matrix, where each column is a separate set of data. Default values for other properties of the object are as follows:

Property |
Default Value |
Description |

Name |
'Mean-square Spectrum' |
Read-only string |

`Frequencies` |
`[]` type ` double` |
Vector of frequencies at which the spectrum is evaluated. The range of this vector depends on the `SpectrumType` value. For a one-sided spectrum, the default range is [0, pi) or [0, `Fs` /2) for odd length, and [0, pi] or [0, `Fs` /2] for even length, if `Fs` is specified. For a two-sided spectrum, it is [0, 2pi) or [0, `Fs` ). The length of the `Frequencies` vector must match the length of the columns of `Data` .If you do not specify `Frequencies` , a default vector is created. If one-sided is selected, then the whole number of FFT points (nFFT) for this vector is assumed to be even.If `onesided` is selected and you specify `Frequencies` , the last frequency point is compared to the next-to-last point and to pi (or `Fs` /2, if `Fs` is specified). If the last point is closer to pi (or `Fs` /2) than it is to the previous point, nFFT is assumed to be even. If it is closer to the previous point, nFFT is assumed to be odd. |

`Fs` |
``Normalized'` |
Sampling frequency, which is `'Normalized'` if `NormalizedFrequency` is `true` . If `NormalizedFrequency` is `false` `Fs` defaults to `1` Hz. |

`SpectrumType` |
`'Onesided'` |
Nyquist interval over which the power spectrum is calculated. Valid values are `'Onesided'` and `'Twosided'` . See the `onesided` and `twosided` methods in `dspdata` for information on changing this property.The interval for `Onesided` is [0 pi) or [0 pi] depending on the number of FFT points, and for `Twosided` the interval is [0 2pi). |

`NormalizedFrequency` |
`true` |
Whether the frequency is normalized (`true` ) or not (`false` ). This property is set automatically at construction time based on `Fs` . If `Fs` is specified, `NormalizedFrequency` is set to `false` . See the `normalizefreq` method in `dspdata` for information on changing this property. |

```
Hmss = dspdata.msspectrum(Data,Frequencies)
```

uses the power spectrum data contained in `Data`

and `Frequencies`

vectors.

```
Hmss = dspdata.msspectrum(...,'Fs',Fs)
```

uses the sampling frequency `Fs`

. Specifying `Fs`

uses a default set of linear frequencies (in `Hz`

) based on `Fs`

and sets `NormalizedFrequency`

to `false`

.

```
Hmss = dspdata.msspectrum(...,'SpectrumType',SpectrumType)
```

uses the `SpectrumType`

string to specify the interval over which the power spectrum was calculated. For data that ranges from [0 pi) or [0 pi], set the `SpectrumType`

to `onesided`

; for data that ranges from [0 2pi), set the the `SpectrumType`

to `twosided`

.

`Hmss`

uses the value of ** = **dspdata.msspectrum(...,'CenterDC',flag)
`flag`

to indicate whether the zero-frequency (DC) component is centered. If `flag`

is `true,`

it indicates that the DC component is in the center of the two-sided spectrum. Set the `flag`

to `false`

if the DC component is on the left edge of the spectrum.

**Methods**

Methods provide ways of performing functions directly on your `dspdata`

object without having to specify the parameters again. You can apply a method directly on the variable you assigned to your `dspdata.msspectrum`

object. You can use the following methods with a `dspdata.msspectrum`

object.

For example, to normalize the frequency and set the `NormalizedFrequency`

parameter to true, use

For detailed information on using the methods and plotting the spectrum, see the `dspdata`

reference page.

**Examples**

This example shows how to view the spectral content of two sinusoids with random noise.

Fs = 32e3; t = 0:1/Fs:2.96; x = cos(2*pi*t*1.24e3)+cos(2*pi*t*10e3)+randn(size(t)); X = fft(x); P = (abs(X)/length(x)).^2; % Compute the mean-square. % Create data object. Hmss = dspdata.msspectrum(P,'Fs',Fs,'centerdc',true); plot(Hmss); % Plot the mean-square spectrum.

**See Also**

`dspdata.psd`

, `dspdata.pseudospectrum`

, `spectrum`

dspdata | dspdata.psd |

© 1994-2005 The MathWorks, Inc.