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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
Weighted Energy Detection for Noncoherent Ultra-Wideband Receiver Design
Feng Wang,Zhi Tian,B M Sadler +2 more
TL;DR: Simulations show that the proposed noncoherent WED receiver enhances the bit-error-rate performance compared to conventional energy detectors.
Journal ArticleDOI
Positioning with OFDM signals for the next- generation GNSS
TL;DR: Computer simulations verify that the positioning accuracy of the proposed algorithm with bearable complexity can reach the Cramer-Rao lower bound (CRLB) in the range of medium to high signal-to-noise ratio (SNR).
Journal ArticleDOI
Automatic Transcription of Guitar Chords and Fingering From Audio
TL;DR: The method was evaluated on recordings from the acoustic, electric, and the Spanish guitar and clearly outperformed a non-guitar-specific reference chord transcription method despite the fact that the number of chords considered here is significantly larger.
Journal ArticleDOI
The correntropy MACE filter
TL;DR: The correntropy MACE (CMACE) can potentially improve upon the MACE performance while preserving the shift-invariant property and outperforms the linear MACE in both generalization and rejection abilities.
Journal ArticleDOI
Robust Estimators for Multipass SAR Interferometry
Yuanyuan Wang,Xiao Xiang Zhu +1 more
TL;DR: This paper introduces a framework for robust parameter estimation in multipass interferometric synthetic aperture radar (InSAR), such as persistent scatterer interferometry, SAR tomography, small baseline subset, and SqueeSAR, and can be easily extended to other multipass InSAR techniques, particularly to those where covariance matrix estimation is vital.
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.