scispace - formally typeset
Proceedings ArticleDOI

Probability distribution of steady-state errors and adaptation over networks

Reads0
Chats0
TLDR
In this paper, the authors derive a near-optimal combination rule for adaptation over networks, which is used to combine the estimators across neighbors within a network, is near optimal in the minimum variance unbiased sense.
Abstract
In this work, we derive a near-optimal combination rule for adaptation over networks. To do so, we first establish a useful result pertaining to the steady-state distribution of the estimator of an LMS filter. Specifically, under small step-sizes and some conditions on the data, we show that the steady-state estimator is approximately Gaussian and provide an expression for its covariance matrix. The result is subsequently used to show that the maximum ratio combining rule over networks, which is used to combine the estimators across neighbors within a network, is near optimal in the minimum variance unbiased sense. The result suggests a rule for combining the estimators within neighborhoods that can lead to improved mean-square error performance.

read more

Citations
More filters
Journal ArticleDOI

On the Learning Behavior of Adaptive Networks—Part II: Performance Analysis

TL;DR: In this paper, the authors examined the mean-square stability and convergence of the learning process of distributed strategies over graphs and identified conditions on the network topology, utilities, and data in order to ensure stability; the results also identified three distinct stages in the learning behavior of multiagent networks related to transient phases I and II and the steady state phase.
Journal ArticleDOI

Diffusion-Based Adaptive Distributed Detection: Steady-State Performance in the Slow Adaptation Regime

TL;DR: A fundamental scaling law is established for the steady-state probabilities of miss detection and false alarm in the slow adaptation regime, when the agents interact with each other according to distributed strategies that employ small constant step-sizes.
Journal ArticleDOI

Diffusion-Based Adaptive Distributed Detection: Steady-State Performance in the Slow Adaptation Regime

TL;DR: In this article, a scaling law for the steady-state probabilities of miss detection and false alarm in the slow adaptation regime was established for distributed detection schemes over fully decentralized networks, where the agents interact with each other according to distributed strategies that employ small constant step-sizes.
Journal ArticleDOI

Decentralized Clustering and Linking by Networked Agents

TL;DR: This work proposes a decentralized clustering algorithm aimed at identifying and forming clusters of agents of similar objectives, and at guiding cooperation to enhance the inference performance, and illustrates the performance of the proposed method in comparison to other useful techniques.
Proceedings ArticleDOI

Large deviations analysis of adaptive distributed detection

TL;DR: This work shows how to design and characterize the performance of diffusion strategies that reconcile both needs of adaptation and detection in decentralized systems using the powerful tool of large deviations analysis.
References
More filters
Book

Table of Integrals, Series, and Products

TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform

A table of integrals

TL;DR: Basic Forms x n dx = 1 n + 1 x n+1 (1) 1 x dx = ln |x| (2) udv = uv − vdu (3) 1 ax + bdx = 1 a ln|ax + b| (4) Integrals of Rational Functions
Book

Random variables and stochastic processes

TL;DR: An electromagnetic pulse counter having successively operable, contact-operating armatures that are movable to a rest position, an intermediate position and an active position between the main pole and the secondary pole of a magnetic circuit.
Book

Adaptive Filters

Ali H. Sayed
TL;DR: Adaptive Filters offers a fresh, focused look at the subject in a manner that will entice students, challenge experts, and appeal to practitioners and instructors.
Related Papers (5)