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Fundamentals Of Statistical Signal Processing
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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.read more
Citations
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Journal ArticleDOI
Estimation of unknown structure parameters from high-resolution (S)TEM images: what are the limits?
TL;DR: Alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers, to show the practical use for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images.
Journal ArticleDOI
Localization in vehicular ad hoc networks using data fusion and V2V communication
TL;DR: A novel approach based on the idea of cooperative localization is proposed, which incorporates different techniques of localization along with data fusion as well as vehicle-to-vehicle communication, to integrate the available data and cooperatively improve the accuracy of the localization information of the vehicles.
Journal ArticleDOI
On Spatial Domain Cognitive Radio Using Single-Radio Parasitic Antenna Arrays
D. Wilcox,Elpiniki Tsakalaki,Ayse Kortun,Tharmalingam Ratnarajah,Constantinos B. Papadias,Mathini Sellathurai +5 more
TL;DR: An adaptive beamforming algorithm is developed to capitalise on directional transmit opportunities which do not interfere with active PUs and efficiently utilise the spatial domain, which numerically optimises the beampattern and antenna efficiency using a convex formulation.
Journal ArticleDOI
Noncontact ultrasonic guided wave inspection of rails
Stefano Mariani,Thompson V. Nguyen,Robert Phillips,Piotr Kijanka,Francesco Lanza di Scalea,Wieslaw J. Staszewski,Mahmood Fateh,Gary Carr +7 more
TL;DR: In this article, the authors describe a new system for high-speed and noncontact rail integrity evaluation being developed at the University of California at San Diego, which uses a specialized filtering approach due to the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel.
Journal ArticleDOI
Nonparametric Basis Pursuit via Sparse Kernel-Based Learning: A Unifying View with Advances in Blind Methods
TL;DR: In this paper, the authors propose a framework for sparse kernel-based learning (KBL) approaches leveraging sparse linear regression, nuclear-norm regularization, and dictionary learning, which goes beyond translating sparse parametric approaches to their nonparametric counterparts.
References
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Book
Adaptive Filter Theory
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.