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dsp.AnalyticSignal

Analytic signals of discrete-time inputs

Description

The dsp.AnalyticSignal System object™ computes analytic signals of discrete-time inputs. The real part of the analytic signal in each channel is a replica of the real input in that channel, and the imaginary part is the Hilbert transform of the input. In the frequency domain, the analytic signal doubles the positive frequency content of the original signal while zeroing-out negative frequencies and retaining the DC component.

The object computes the Hilbert transform using an equiripple FIR filter or a Kaiser window FIR filter. When the filter order is low, the object uses an equiripple FIR filter. For higher filter orders, if the equiripple design fails, the object uses a Kaiser window FIR filter.

To compute the analytic signal of a discrete-time input:

  1. Create the dsp.AnalyticSignal object and set its properties.

  2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

This object supports C/C++ code generation and SIMD code generation under certain conditions. For more information, see Code Generation.

Creation

Description

anaSig = dsp.AnalyticSignal returns an analytic signal object, anaSig, that computes the complex analytic signal corresponding to each channel of a real M-by-N input matrix.

anaSig = dsp.AnalyticSignal(order) returns an analytic signal object, anaSig, with the FilterOrder property set to order.

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anaSig = dsp.AnalyticSignal(Name=Value) sets properties using one or more name-value arguments. For example, to specify the filter order used to compute Hilbert transform as 24, set FilterOrder to 24.

Properties

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Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

Order of the FIR filter used in computing the Hilbert transform, specified as an even positive integer greater than 3. For lower filter orders, the object uses an equiripple FIR filter to compute the Hilbert transform. For higher filter orders, if the equiripple design fails, the object uses a Kaiser window FIR filter instead.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Usage

Description

y = anaSig(x) computes the analytic signal, y, of the M-by-N input matrix x, according to the equation

Y=X+jH{X}

where j is the imaginary unit and H{X} denotes the Hilbert transform.

Each of the N columns in x contains M sequential time samples from an independent channel. The method computes the analytic signal for each channel.

example

Input Arguments

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Data input, specified as a vector or a matrix.

Data Types: single | double
Complex Number Support: Yes

Output Arguments

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Analytic signal output, returned as a vector or a matrix.

Data Types: single | double
Complex Number Support: Yes

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

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stepRun System object algorithm
releaseRelease resources and allow changes to System object property values and input characteristics
resetReset internal states of System object

Examples

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Compute the analytic signal of a sinusoidal input.

t = (-1:0.01:1)';
x = sin(4*pi*t);
anaSig = dsp.AnalyticSignal(200);
y = anaSig(x);

View the analytic signal.

subplot(2,1,1);
plot(t, x)
title('Original Signal');
subplot(2,1,2), plot(t, [real(y) imag(y)]);
title('Analytic signal of the input')
legend('Real signal','Imaginary signal',...
    'Location','best');

Figure contains 2 axes objects. Axes object 1 with title Original Signal contains an object of type line. Axes object 2 with title Analytic signal of the input contains 2 objects of type line. These objects represent Real signal, Imaginary signal.

More About

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Algorithms

The algorithm computes the Hilbert transform with an equiripple FIR for the specified order n using the Remez exchange algorithm. For higher filter orders, if the equiripple design fails, the algorithm uses a Kaiser window FIR filter instead. In both cases, the filter has a linear phase with a constant group delay of n/2 input samples.

Extended Capabilities

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Version History

Introduced in R2012a

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See Also

Objects