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Processing Data by Blocks In most efficient implementations we process data by blocks, rather than one sample at a time. Real Time simulation and design.

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Presentation on theme: "Processing Data by Blocks In most efficient implementations we process data by blocks, rather than one sample at a time. Real Time simulation and design."— Presentation transcript:

1 Processing Data by Blocks In most efficient implementations we process data by blocks, rather than one sample at a time. Real Time simulation and design software such as Simulink are designed to take advantages of block processing for two purposes: efficient computations, thus faster simulations; efficient design.

2 “Sample Based” and “Frame Based” Signals Sample Based: time They are MN distinct signals arranged in a matrix Particular Case: is like M distinct signals

3 “Sample Based” and “Frame Based” Signals Frame Based: They are N distinct signals, each one represented as a sequence of frames of length M Particular Case: one signal as a sequence of frames of length M

4 y0=Frame based y1=Sample based y2=y0=Frame based Convert “to Sample” and “to Frame” Example:

5 Serial to Parallel (Buffer)

6 Serial to Parallel in Simulink Serial to Parallel is implemented by the “Buffer” Simulink block in Signal Processing Blcokset > Signal Management > Buffers: S/P Sample based Frame based

7 Example of Downsampling

8 Parallel to Serial (Unbuffer or Interlacer)

9 Parallel to Serial in Simulink Parallel to Serial is implemented by the “UnBuffer” Simulink block in Signal Processing Blcokset > Signal Management > Buffers: Frame based Sample based P/S

10 Example of Upsampling

11 Simulink Implementation N channel to N channel IFFT: Sample based Frame Sample

12 M channel Parallel to Serial with Unbuffer: UNBUFFER

13 Everything sample based Simulink Implementation N channel to N channel FFT:

14 M channel Serial to Parallel with Buffer: BUFFER


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