Sources for 1D Signal Decimation - Books & URLs

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SUMMARY

This discussion focuses on sourcing materials for understanding one-dimensional signal decimation, specifically for implementation in MATLAB or C. The user is already familiar with the "decimate" function in MATLAB and seeks theoretical knowledge to develop a custom function. Key concepts include the relationship between decimation filtering and downsampling, emphasizing the importance of filtering before downsampling to avoid aliasing and reduce memory usage when storing FIR data.

PREREQUISITES
  • Understanding of MATLAB programming, particularly the "decimate" function.
  • Knowledge of FIR (Finite Impulse Response) filters and their coefficients.
  • Familiarity with signal processing concepts, including downsampling and aliasing.
  • Basic understanding of C programming for implementing signal processing algorithms.
NEXT STEPS
  • Research the theory behind FIR filters and their implementation in MATLAB.
  • Learn about aliasing and techniques to prevent it during signal processing.
  • Explore MATLAB's signal processing toolbox for advanced functions related to decimation.
  • Study C programming techniques for efficient signal processing algorithms.
USEFUL FOR

Signal processing engineers, MATLAB developers, and C programmers interested in implementing efficient decimation algorithms and understanding the underlying theory.

makris
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Can anybody tell a few good sources for 1dimentional signal decimation? Either books or URLs?

I know how to use the "decimate" function in MATLAB thus perform decimation, but my goal is to code a function in MATLAB (or C) to perform the same process. That is why I need the theory behind decimation.

Thanks
 
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i don't know your application but in decimation filtering and down sampling is perform in a paralle way . suppose if we down sample first and then we will filter with low pass filter we have to face alising while if we do filtering first then down sample then also it its useless as we have to spend a lots of memory to store the FIR data so what we do is every time when we delay signal by one sample,we down sample it and multiply it with FIR coeeficient in this way we acchieve both the things

y(n)=[N-1]\sum[i=1]h(i)*X(Mn-i);

i know its a bit confussing but try to google
 

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