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Journal ArticleDOI

Fundamentals of statistical signal processing: Estimation theory: by Steven M. KAY; Prentice Hall signal processing series; Prentice Hall; Englewood Cliffs, NJ, USA; 1993; xii + 595 pp.; $65; ISBN: 0-13-345711-7

K.Venkatesh Prasad
- 01 Aug 1994 - 
- Vol. 2, Iss: 4, pp 728
About
This article is published in Control Engineering Practice.The article was published on 1994-08-01. It has received 337 citations till now. The article focuses on the topics: Statistical signal processing.

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Citations
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Journal ArticleDOI

The elusive Heisenberg limit in quantum-enhanced metrology

TL;DR: It is shown that when decoherence is taken into account, the maximal possible quantum enhancement in the asymptotic limit of infinite N amounts generically to a constant factor rather than quadratic improvement.

A Survey of Spectral Unmixing Algorithms

TL;DR: This article distills spectral unmixing algorithms into a unique set and surveys their characteristics through hierarchical taxonomies that reveal the commonalities and differences between algorithms.
Journal ArticleDOI

Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design

TL;DR: In this article, the authors derived closed-form expressions for the user rates and a scaling law that shows how fast the hardware imperfections can increase with $N$ while maintaining high rates.
Journal ArticleDOI

Power scheduling of universal decentralized estimation in sensor networks

TL;DR: The proposed power scheduling scheme suggests that the sensors with bad channels or poor observation qualities should decrease their quantization resolutions or simply become inactive in order to save power.
Journal ArticleDOI

A constrained least squares approach to mobile positioning: algorithms and optimality

TL;DR: This paper presents a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases and shows that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small.
References
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Journal ArticleDOI

The elusive Heisenberg limit in quantum-enhanced metrology

TL;DR: It is shown that when decoherence is taken into account, the maximal possible quantum enhancement in the asymptotic limit of infinite N amounts generically to a constant factor rather than quadratic improvement.

A Survey of Spectral Unmixing Algorithms

TL;DR: This article distills spectral unmixing algorithms into a unique set and surveys their characteristics through hierarchical taxonomies that reveal the commonalities and differences between algorithms.
Journal ArticleDOI

Power scheduling of universal decentralized estimation in sensor networks

TL;DR: The proposed power scheduling scheme suggests that the sensors with bad channels or poor observation qualities should decrease their quantization resolutions or simply become inactive in order to save power.
Journal ArticleDOI

A constrained least squares approach to mobile positioning: algorithms and optimality

TL;DR: This paper presents a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases and shows that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small.
Journal ArticleDOI

Neuronal tuning: to sharpen or broaden

TL;DR: A general rule is derived for how the Fisher information scales with the tuning width, regardless of the exact shape of the tuning function, the probability distribution of spikes, and allowing some correlated noise between neurons.