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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
Noise Tracking Using DFT Domain Subspace Decompositions
TL;DR: A novel approach for noise tracking, which updates the noise PSD for each DFT coefficient in the presence of both speech and noise, based on the eigenvalue decomposition of correlation matrices that are constructed from time series of noisy DFT coefficients is presented.
Journal ArticleDOI
Acoustic Source Localization and Beamforming: Theory and Practice
TL;DR: The theoretical and practical aspects of locating acoustic sources using an array of microphones are considered, and a maximum-likelihood (ML) direct localization is obtained when the sound source is near the array, while in the far-field case, the localization via the cross bearing from several widely separated arrays is demonstrated.
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Storage of environmental samples for guaranteeing nucleic acid yields for molecular microbiological studies
TL;DR: Preservation in phenol–chloroform solution can be recommended as an alternative storage method when freezing is not possible such as during extended field sampling; however, ethanol and RNAlater® may cause serious problems when used as preservatives for environmental samples containing humic acids.
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Optimal Spectral Feature Detection for Spectrum Sensing at Very Low SNR
TL;DR: Simulation results show that the proposed sensing technique can reliably detect analog and digital TV signals at SNR levels as low as -20 dB, and the spectral correlation-based detector is asymptotically optimal according to the Neyman-Pearson criterion.
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Compressed sensing techniques for detecting damage in structures
TL;DR: The suitability of compressed sensing to address structural health monitoring challenges is established, and a compressed version of the matched filter known as the smashed filter has been implemented on-board the sensor node, and its suitability for detecting structural damage will be discussed.
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.