The imaginary component of a Fast Fourier Transform (FFT) calculated using blocking.  There are two forms.

Note: This item is deprecated and will be removed in a future release.

Syntax

Imag_part = BlockFftImag(vec1, vec2, block_size, overlap)

Imag_part = BlockFftImag(vec1, vec2, window, overlap)

Arguments

Name

Description

vec1

A vector of the real components of time domain data.

vec2 (optional)

A vector of the imaginary components of time domain data. The vector is of type real.

block_size

The number of elements to be used for each FFT (should be a power of 2).  Must be a positive integer and not greater than the length of vec.

window

A vector of window weights to apply to each block. Should be of length of power of 2. This length is used as the block size.

overlap

The number of elements shared between consecutive blocks. Must be a non-negative integer and less than block_size.

Output

Name

Description

Imag_part

A vector of the imaginary component of the FFT.

Example 1

Find the imaginary component of the FFT of a signal stored in vector data, using a block size of 256 and an overlap of 128.

Syntax

output = BlockFftImag(data, 256, 128)

Result

output is a vector of the imaginary components.

Example 2

Repeat the above example with a Hanning window instead.

Syntax

output = BlockFftImag(data, HannWin(256), 128)

Results

output is a vector of the imaginary components.

Comments

The BlockFftImag function uses blocking to calculate the imaginary component of a Fast Fourier Transform (FFT).  The FFT is complex-valued and used to map time-domain data into the frequency domain. vec1 and vec2 are assumed to be evenly sampled.  The resultant vector has a number of elements equal to the least power of two greater than or equal to the block_size.

The BlockFftImag function is different from a normal FFT in that it introduces blocking.  The input vector is subdivided into blocks, each having block_size number of elements.  An FFT is then performed on each individual block.  The results of these FFTs are then averaged to give the final result.

See Also:

BlockFftMag

BlockFftPhase

BlockFftReal

Fold

Freq