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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
Passive Imaging of Moving Targets Using Sparse Distributed Apertures
Ling Wang,Birsen Yazici +1 more
TL;DR: A new passive imaging method for moving targets in free space using measurements from a sparse array of receivers that rely on illumination sources of opportunity to address the image formation as a generalized likelihood ratio test for an unknown target position and velocity.
Journal ArticleDOI
A new detector for contourlet domain multiplicative image watermarking using Bessel K form distribution
TL;DR: This paper proposes a novel multiplicative contourlet domain watermark detector based on using the Maximum Likelihood (ML) decision rule and BKF distribution and demonstrates the high efficiency of Bessel K form (BKF) distribution to model these coefficients.
Journal ArticleDOI
Spectrum sensing based on fractional lower order moments for cognitive radios in α-stable distributed noise
TL;DR: Analytical and simulation results show that the proposed FLOM detector has a much better performance than the Cauchy detector in the α-stable distributed noise environment and it is shown that multi-user cooperative sensing leads to a significantly higher probability of detection than the single user version.
Journal ArticleDOI
Blind Minimax Estimation
Zvika Ben-Haim,Yonina C. Eldar +1 more
TL;DR: The approach does not require any prior assumption or knowledge, and the proposed estimator can be applied to any linear regression problem, and can be readily extended to a wider class of estimation problems than Stein's estimator, which is defined only for white noise and nontransformed measurements.
Journal ArticleDOI
Derived PDF of maximum likelihood signal estimator which employs an estimated noise covariance
TL;DR: It is demonstrated that there exists a dynamic tradeoff between signal-to-noise ratio (SNR) and noise adaptivity as the dimensionality of the array data is varied, suggesting the existence of an optimal array data dimension that will yield the best performance.
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.