System Maximizer

  • Block Diagram editor
  • High Speed Simulator
  • Integrated Graphing and Measurement
  • Library of Parameterizable Digital Signal Processing Elements
  • User Custom Elements
  • Importing / Exporting Data

Requirements

  • Mac OS X 10.4
  • 1024 x 768 display

Recommended

  • Intel Core Duo Processor
  • or
  • 1GHz G5 or Better Processor
  • or
  • 1GHz G4 or Better Processor

 



FIR Coefficient Finder

  • Quickly Design FIR Filters
  • Floating Point - Fixed Point Conversion
  • Multiple Filter Types
  • Window and Parks McLellan algorithms
  • Time and Frequency Plots
  • Cursors To Measure Performance
  • up to 2047 coefficients

Requirements

  • Mac OS X 10.4
  • 1024 x 768 display

Recommended

  • Intel Core Duo Processor
  • or
  • 1GHz G5 or Better Processor
  • or
  • 1GHz G4 or Better Processor

 


About Optunis

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Learn DSP @ Optunis.com


DSP Fundamentals - 101 - Fourier Analysis (members only) Download a printable PDF
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The Fourier transform has several interesting properties.

Linearity means that if we can add two signals in time, their Fourier transforms will also add. If we amplify or attenuate a signal in time, its Fourier transform will also amplify or attenuate by the same amount.

If a signal is real in time, it will be complex conjugate symmetric. This means, that we only really need to look at half the Fourier transform.

Time shifting, will be described in detail in a later slide.

Shifting the frequency of a signal is the same as multiplying the signal in time by a rotating complex exponential

Finally, multiplying two signal in the frequency domain is the same as complicated process called convolution in the time domain.



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