User`s guide

1 Introduction
1-4
into all of its blocks. A completely frame-based model can run several times
faster than the same model processing sample-by-sample; faster still if data
sources are frame based.
See “Sample Rates and Frame Rates” on page 3-16 for more information.
Matrix Support
The DSP Blockset takes full advantage of Simulink’s matrix format. Some
typical uses of matrices in DSP simulations are:
•General two-dimensional array
A matrix can be used in its traditional mathematical capacity, as a simple
structured array of numbers. Most blocks for general matrix operations are
found in the Matrices and Linear Algebra library.
•Factored submatrices
A number of the matrix factorization blocks in the Matrix Factorizations
library store the submatrix factors (i.e., lower and upper submatrices) in a
single compound matrix. See the LDL Factorization and LU Factorization
blocks for examples.
•Multichannel frame-based signal
The standard format for multichannel frame-based data is a matrix
containing each channel’s data in a separate column. A matrix with three
columns, for example, contains three channels of data, one frame per
channel. The number of rows in such a matrix is the number of samples in
each frame.
See the following sections for more information about working with matrices:
•“Multichannel Signals” on page 3-11
•“Creating Signals” on page 3-33
•“Constructing Signals” on page 3-42
•“Importing Signals” on page 3-62
Adaptive and Multirate Filtering
The Adaptive Filters and Multirate Filters libraries provide key tools for the
construction of advanced DSP systems. Adaptive filter blocks are
parameterized to support the rapid tailoring of DSP algorithms to
application-specific environments, and effortless “what if” experimentation.