#esprit-algorithm

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#spectral-estimation #error-scaling #signal-processing #central-limit-error #parameter-estimation
fromHackernoon
10 months ago

References: Spectral Estimation, Signal Processing, and Quantum Computing | HackerNoon

The ESPRIT algorithm provides a method for estimating the parameters of a deterministic signal model, showcasing its efficacy in error scaling and eigenvalue analysis.
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fromHackernoon
10 months ago

Explicit Expansion and Bounds of Spectral Projector in ESPRIT Analysis | HackerNoon

The article details methods for bounding higher-order terms in perturbation expansions related to spectral projectors.
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fromHackernoon
10 months ago

Strong Eigenvector Comparison for Optimal ESPRIT Convergence | HackerNoon

The ESPRIT algorithm's optimal convergence rate hinges on a strong eigenvector comparison theorem.
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fromHackernoon
10 months ago

New Technical Advancements in ESPRIT Spectral Analysis | HackerNoon

The ESPRIT algorithm enhancements may impact broader subspace-based signal processing methodologies.
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fromHackernoon
10 months ago

Proof of Central Limit Error Scaling for ESPRIT Algorithm | HackerNoon

The ESPRIT algorithm achieves optimal error scaling under central limit scaling, improving prior work and facilitating spectral estimation.
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fromHackernoon
10 months ago

Optimal Error Scaling of ESPRIT Algorithm Demonstrated | HackerNoon

The paper presents a novel analysis that establishes optimal error scaling for the ESPRIT algorithm.
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