The Mean Square Error (MSE) Performance Criteria

  • S. Thomas Alexander
Part of the Texts and Monographs in Computer Science book series (MCS)


Adaptive signal processing algorithms generally attempt to optimize a performance measure that is a function of the unknown parameters to be identified. The most pervasive of these performance measures are based upon squared prediction errors, although the specific prediction error used in adaptation often depends upon the particular algorithm. Two broad categories of adaptive signal processing methods are: (1) stochastic and (2) exact. The latter category refers to adaptive filters based upon the actual or exact data signals acquired. The recursive least squares techniques comprising Chapters 8–11 are examples of these exact techniques, and investigation of those techniques will be deferred until the later chapters.


Mean Square Error Prediction Error Minimum Mean Square Error Linear Prediction Adaptive Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York Inc. 1986

Authors and Affiliations

  • S. Thomas Alexander
    • 1
  1. 1.Department of Electrical and Computer EngineeringNorth Carolina State UniversityRaleighUSA

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