# Advanced DSP With A Few Tears^{TM}

#### Advanced DSP With A Few Tears^{®} covers theory and applications of advanced statistical DSP algorithms. You will learn how to evaluate and implement advanced DSP alternatives. Focus is on "what you need to know" without unnecessary and often confusing mathematical details.

Basics Matrix review Linear equations Least squares parameter estimation

Random Signals Applications Mean Variance and power relationship Autocorrelation function Wide sense stationary signals Toeplitz autocorrelation matrix White noise Crosscorrelation Linear Prediction Speech application

Adaptive Filtering Wiener Filter LMS Algorithm LMS performance Stability Step size selection Normalized LMS Leaky LMS Signed LMS Constant Modulus Algorithm Recursive Least Squares RLS vs. LMS

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DSP Without Tears^{®}
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