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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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Proceedings ArticleDOI
Exploiting polarization for spectrum sensing in cognitive SatComs
TL;DR: The simulation results show that OPBC technique achieves a great improvement in sensing efficiency over other considered techniques at the expense of complexity in a dual polarized AWGN channel.
Journal ArticleDOI
PyLops—A linear-operator Python library for scalable algebra and optimization
Matteo Ravasi,Ivan Vasconcelos +1 more
TL;DR: It is shown that PyLops operators can dramatically reduce the memory load and CPU computations compared to explicit-matrix calculations, while still allowing users to seamlessly use their existing knowledge of compact matrix-based syntax that scales to any problem size because no explicit matrices are required.
Journal ArticleDOI
Optimal 3-D Landmark Placement for Vehicle Localization Using Heterogeneous Sensors
TL;DR: Numerical results demonstrate that the proposed optimal landmark placement enables accurate AGV localization over significantly large volume or area of the search space compared with the case when landmarks are randomly placed.
Journal ArticleDOI
Alternating Least-Squares for Low-Rank Matrix Reconstruction
TL;DR: In this article, an iterative algorithm based on least-squares estimation is proposed for reconstruction of low-rank matrices from undersampled measurements, which is also capable of exploiting a-priori knowledge of matrix structure.
Journal ArticleDOI
Information-Theoretic Optimal Radar Waveform Design
TL;DR: A useful relationship among the three existing wave form design metrics, namely the output signal-to-noise ratio, the Kullback–Leibler divergence, and the mutual information, is provided and explains the tradeoffs of the various metrics currently used for radar waveform design.
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.