What question did this study set out to answer?

To evaluate and compare the degradation in output mean squared error caused by DC offsets across four variations of the stochastic gradient algorithm in analog adaptive filters.

March 1, 1995IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing

Comparison of DC offset effects in four LMS adaptive algorithms

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To evaluate and compare the degradation in output mean squared error caused by DC offsets across four variations of the stochastic gradient algorithm in analog adaptive filters.
Derived theoretical expressions for output mean squared error in the presence of DC offsets assuming Gaussian probability distributions for input and error signals.
Conducted computer simulations across four variations of the stochastic gradient algorithm to validate theoretical predictions.
Evaluated algorithm trade-offs using output error performance, convergence characteristics, and hardware implementation requirements.
Computer simulations verified theoretical models showing performance degradation in mean squared error due to DC offsets across all four algorithm variations.
Identified algorithm-specific trade-offs between offset-induced error, convergence behavior, and circuit complexity to guide optimal algorithm selection in analog hardware.

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Implication

Comparative simulation study reveals how DC offsets degrade mean squared error across four stochastic gradient algorithms, highlighting trade-offs between hardware cost and filter performance.

Cite This Study

Shoval et al. (1995) studied this question.

synapsesocial.com/papers/6a9ded7bc4cdddd9ce367e44 https://doi.org/10.1109/82.372867

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Implication

Comparative simulation study reveals how DC offsets degrade mean squared error across four stochastic gradient algorithms, highlighting trade-offs between hardware cost and filter performance.

Comparison of DC offset effects in four LMS adaptive algorithms

Key Points

Discussion

Implication

Cite This Study

Comparison of DC offset effects in four LMS adaptive algorithms

Key Points

Discussion

Implication

Cite This Study

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