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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
Methodological principles of T wave alternans analysis: a unified framework
TL;DR: A unified framework is proposed which holds the existing T wave alternans analysis methods and the methodological principles of the published TWA analysis schemes are compared and discussed.
Journal ArticleDOI
Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO
TL;DR: In this article, a tractable uplink energy efficiency (EE) maximization problem was formulated and solved with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor.
Journal ArticleDOI
Clock Synchronization in Wireless Sensor Networks: An Overview
TL;DR: This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization Protocol for W SNs.
Calibration of a MEMS inertial measurement unit
Isaac Skog,Peter Händel +1 more
TL;DR: In this article, an approach for calibrating a low-cost IMU is studied, requiring no mechanical platform for the accelerometercalibration and only a simple rotating table for the gyrocalibration.
Journal ArticleDOI
Efficient gathering of correlated data in sensor networks
TL;DR: Simulation results over randomly generated sensor networks with both artificially and naturally generated data sets demonstrate the efficiency of the designed algorithms and the viability of the technique—even in dynamic conditions.
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.