DSP Blockset

Convolution

Compute the convolution of two inputs.

Library

Signal Operations

Description

The Convolution block convolves corresponding columns (channels) of Mu-by-N input matrix u and Mv-by-N input matrix v.

Frame-Based Inputs

Matrix inputs must be frame-based. The output, y, is a frame-based (Mu+Mv-1)-by-N matrix whose jth column has elements

where * denotes the complex conjugate. Inputs u and v are zero when indexed outside of their valid ranges. When both inputs are real, the output is real; when one or both inputs are complex, the output is complex.

When one input is a column vector (single channel) and the other is a matrix (multiple channels), the single-channel input is independently convolved with each channel of the multichannel input. For example, if u is a Mu-by-1 column vector and v is an Mv-by-N matrix, the output is an (Mu+Mv-1)-by-N matrix whose jth column has elements

Sample-Based Inputs

If u and v are sample-based vectors with lengths Mu and Mv, the Convolution block performs the vector convolution

The dimensions of the sample-based output vector are determined by the dimensions of the input vectors:

• When both inputs are row vectors, or when one input is a row vector and the other is a 1-D vector, the output is a 1-by-(Mu+Mv-1) row vector.
• When both inputs are column vectors, or when one input is a column vector and the other is a 1-D vector, the output is a (Mu+Mv-1)-by-1 column vector.
• When both inputs are 1-D vectors, the output is a 1-D vector of length Mu+Mv-1.

The Convolution block does not accept sample-based full-dimension matrix inputs, or mixed sample-based row vector and column vector inputs.

Dialog Box

See Also

Correlation	DSP Blockset
conv	MATLAB

Convert Complex Simulink To DSP

Correlation