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“MATLAB is a universal language that makes it easy to exchange algorithms and test results across our team. Our physical layer model in MATLAB and Simulink enabled us to better understand the LTE specifications, and Model-Based Design enabled us to verify that our FPGA implementation conformed to those specifications.” —Francisco Javier Campos, AT4 wireless

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"Simulink enables us to easily share proposals and knowledge with other design centers. Simulink also allows us to focus on algorithm design and perform state-of-art mathematical analysis, assessment, simulation, and optimization." - Dr.Thierry Lestable, SERI

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Signal Processing Toolbox

View Data Sheet
Free Technical Kit

Description

Developing Signal Processing Algorithms

Signal Processing Toolbox offers techniques for developing signal processing algorithms in these categories:

  •     Signal transforms, including discrete cosine transform (DCT), Hilbert, Goertzel, and Walsh-Hadamard
  •     Multirate operations for decimation, interpolation, and resampling
  •     Statistical signal processing functions to compute autocorrelation, covariance, cross-correlation, and cross-covariance of signals
  •     Linear prediction and parametric modeling functions

You can use these techniques to explore various algorithm approaches and perform a variety of signal processing tasks. You can:

  •     Interpolate, decimate, or resample a signal
  •     Modulate and demodulate a signal
  •     Smooth a signal using windowing functions
  •     Encode a signal for a compression algorithm

 

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Common signal processing techniques implemented using toolbox functions. Examples include (clockwise from top left): Resampling an audio signal from a DAT sample rate of 48 kHz to a CD sample rate of 44.1 kHz, interpolating a signal by a factor of 4, modulating message signals using double sideband modulation, and encoding floating-point scalars in the range [–1, 1] to uint8 integers.


Creating and Applying Window Functions

Data window functions apply to both spectral analysis and filter design. A window function suppresses the effects of the Gibbs phenomenon that result from truncating an infinite series. The toolbox contains functions for creating and applying several window functions including rectangular, Hamming, Hann, Kaiser, and Gaussian.

The interactive Window Design and Analysis Tool (WinTool) lets you design and analyze spectral windows. You can:

  •     Display time-domain and frequency-domain representations of selected windows
  •     Export window vectors or window objects to the MATLAB workspace, a MAT-file, or a text file
  •     View typical window measurements, such as leakage factor, relative sidelobe attenuation, and main lobe width
  •     Visualize, annotate, and print time-domain and frequency-domain plots

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Window Design and Analysis Tool (WinTool) with time-domain and frequency-domain plots of Hamming, Hann, and Kaiser windows.



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