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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

Copula-Based Fusion of Correlated Decisions

TL;DR: Using a Neyman-Pearson (NP) framework for detection at the fusion center, the optimal fusion rule is derived and results demonstrating the efficiency of the copula-based fusion rule are shown.
Journal ArticleDOI

Robust GNSS Receivers by Array Signal Processing: Theory and Implementation

TL;DR: An overview of the possible receiver architectures encompassing antenna arrays and the associated signal processing techniques is provided, with emphasis on the most typical implementation issues found when dealing with such technology.
Proceedings ArticleDOI

Cognitive Technology for Ultra-Wideband/WiMax Coexistence

TL;DR: This paper explores the use of cognitive technology to enable the operation of ultra-wideband (UWB) devices in WiMax bands and describes the obstacles faced in achieving robust detection and avoidance with an on-chip implementation of basic DAA functionality.
Dissertation

Direction finding in the presence of mutual coupling

T. Svantesson
TL;DR: The coupling in a Uniform Linear Array of thin and nite dipoles is calculated using basic electromagnetic concepts and it is found that estimating the coupling along with the DOAs mitigates the e ects of an unknown coupling.
Journal ArticleDOI

Optimal Placement of Piezoelectric Actuators and Sensors for Detecting Damage in Plate Structures

TL;DR: In this article, the authors proposed an approach for optimal actuator and sensor placement for active sensing-based structural health monitoring based on ultrasonic wave propagation for detecting damage in thin plate-like structures.
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.