Signal processing + parameter estimation

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SUMMARY

Parameter estimation in Digital Signal Processing (DSP) is integral for applications such as bit error rates and maximum likelihood detection. It involves adjusting parameters within mathematical models to enhance control laws and improve confidence intervals on error estimates. The discussion highlights that maximum likelihood is a significant method used in parameter estimation, with various estimators yielding dramatically different results, particularly in signal detection capabilities. Resources like Digital Calculus provide tools for comparing these estimators and their effectiveness.

PREREQUISITES
  • Understanding of Digital Signal Processing (DSP) concepts
  • Familiarity with maximum likelihood estimation techniques
  • Knowledge of adaptive control systems
  • Basic proficiency in mathematical modeling and parameter tuning
NEXT STEPS
  • Explore maximum likelihood estimation in DSP applications
  • Research adaptive control models and their parameter estimation techniques
  • Learn about the effects of zero padding in signal processing
  • Investigate tools available on Digital Calculus for parameter estimation comparisons
USEFUL FOR

Engineers, researchers, and students in the fields of digital signal processing, control systems, and communications who are looking to deepen their understanding of parameter estimation techniques and their practical applications.

JamesGoh
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Is parameter estimation in DSP concerned with things such as bit error rates, maximum likelihood detection etc ... ?

If not, can someone point me in the right direction so I can find some learning material.

thanks
 
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when i used parameter estimation (many many years ago), it was part of an adaptive controller model. that is, estimate parameters to adjust the control law, and over time get tighter control and a tighter confidence interval on the error of your control law estimates. our modelling was not related to communications, but the theory for the parameter estimation should be covered in standard graduate-level digital controls courses, i think.
 
JamesGoh said:
Is parameter estimation in DSP concerned with things such as bit error rates, maximum likelihood detection etc ... ?

Yes those are parameters that some may like to play with; i.e. tweak. If you have a math model with any parameters that you want to tweak then these are parameter estimations. In http://www.digitalCalculus.com/misc/calculus-programming.html" most math models have parameters that are tweated by a 'find' statement.

For DSP, there are a dozen http://www.digitalCalculus.com/demo/rainbow.html" in one program to compare results. Maximum likelihood is one of the methods available. Results differ dramatically between estimators. See effects of zero padding. Some estimators can detect signals 50 to 100 dB from main signal.
 
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