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Fundamentals Of Statistical Signal Processing

Steven Kay
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The article was published on 2001-03-16 and is currently open access. It has received 7058 citations till now. The article focuses on the topics: Statistical signal processing.

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Citations
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Journal ArticleDOI

A Novel Ship Detector Based on the Generalized-Likelihood Ratio Test for SAR Imagery

TL;DR: Ship detection with synthetic aperture radar (SAR) images, acquired at different working frequencies, is presented in this paper where a novel technique is proposed based on the generalized-likelihood ratio test (GLRT).
Journal ArticleDOI

Alleviating Sensor Position Error in Source Localization Using Calibration Emitters at Inaccurate Locations

TL;DR: When deploying multiple calibration emitters, although their positions may not be known exactly, it is possible to completely eliminate the sensor position error and recover the best localization accuracy that is limited by the measurement noise in TDOAs only.
Proceedings ArticleDOI

802.11ec: collision avoidance without control messages

TL;DR: 802.11ec achieves a vast efficiency gain in conveying control information and resolves key throughput and fairness problems in the presence of hidden terminals, asymmetric topologies, and general multihop topologies.
Journal ArticleDOI

Financial fraud detection using vocal, linguistic and financial cues

TL;DR: Optimization results reveal that only a subset of the complete set of numeric, linguistic and vocalic predictors enhance overall predictive accuracy, which should assist investors, financial analysts and regulators in identifying the most effective markers of corporate fraud.
Journal ArticleDOI

Data distributions in magnetic resonance images: a review.

TL;DR: This review paper provides an overview of the various distributions that occur when dealing with MR data, considering both single-coil and multiple- coil acquisition systems and summarizes how knowledge of the MR data distributions can be used to construct optimal parameter estimators.
References
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Book

Adaptive Filter Theory

Simon Haykin
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Journal ArticleDOI

Fundamentals of statistical signal processing: estimation theory

TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Book

Probability, random variables and stochastic processes

TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Book

Probability, random variables, and stochastic processes

TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
Book

Discrete-Time Signal Processing

TL;DR: In this paper, the authors provide a thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete time Fourier analysis.