Results 271 to 280 of about 14,949,583 (325)
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Rapid Convergence Rate in Adaptive Arrays
IEEE Transactions on Aerospace and Electronic Systems, 1974I. Reed, J. Mallett, L. Brennan
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A Novel Value Iteration Scheme With Adjustable Convergence Rate
IEEE Transactions on Neural Networks and Learning Systems, 2022In this article, a novel value iteration scheme is developed with convergence and stability discussions. A relaxation factor is introduced to adjust the convergence rate of the value function sequence.
Mingming Ha, Ding Wang, Derong Liu
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Convergence rate analysis of distributed optimization with projected subgradient algorithm
Automatica, 2017Shuai Liu, Zhirong Qiu, Lihua Xie
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Seismic behaviour of mountain belts controlled by plate convergence rate
Earth and Planetary Science Letters, 2018L. Zilio +3 more
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IEEE transactions on industrial electronics (1982. Print), 2019
Iterative feedback tuning (IFT) enables the data-based optimization of feedback controller parameters without the plant model and disturbance model.
Min Li +5 more
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Iterative feedback tuning (IFT) enables the data-based optimization of feedback controller parameters without the plant model and disturbance model.
Min Li +5 more
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Verification of Reduced Convergence Rates
Computing, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Hsin-Yun, Li, Zi-Cai
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1990
In this chapter, the rate of convergence of the algorithm to its ODE and/or to the desired value θ* is described in more detail. The analysis is again asymptotic.
Albert Benveniste +2 more
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In this chapter, the rate of convergence of the algorithm to its ODE and/or to the desired value θ* is described in more detail. The analysis is again asymptotic.
Albert Benveniste +2 more
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1978
In Section 7.1, rate of convergence is defined, and our approach to the rate problem discussed. The rates are developed (in Section 7.3) for three separate cases, two forms of the basic KW procedure and the basic RM procedure. These algorithms are discussed in Section 7.1 and are put into a form which will be useful in the subsequent development.
Harold J. Kushner, Dean S. Clark
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In Section 7.1, rate of convergence is defined, and our approach to the rate problem discussed. The rates are developed (in Section 7.3) for three separate cases, two forms of the basic KW procedure and the basic RM procedure. These algorithms are discussed in Section 7.1 and are put into a form which will be useful in the subsequent development.
Harold J. Kushner, Dean S. Clark
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Effects of heterogeneous convergence rate on consensus in opinion dynamics
Physica A: Statistical Mechanics and its Applications, 2018The Deffuant model has attracted much attention in the study of opinion dynamics. Here, we propose a modified version by introducing into the model a heterogeneous convergence rate which is dependent on the opinion difference between interacting agents ...
Changwei Huang +5 more
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1997
The traditional definition of rate of convergence refers to the asymptotic properties of normalized errors about the limit point \( \bar \theta \). If e n = e for the Robbins—Monro algorithm, it is concerned with the asymptotic properties of \( U_n^ \in = \left( {\theta _n^ \in - \bar \theta } \right)/\sqrt \in \) for large n and small ∈.
Harold J. Kushner, G. George Yin
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The traditional definition of rate of convergence refers to the asymptotic properties of normalized errors about the limit point \( \bar \theta \). If e n = e for the Robbins—Monro algorithm, it is concerned with the asymptotic properties of \( U_n^ \in = \left( {\theta _n^ \in - \bar \theta } \right)/\sqrt \in \) for large n and small ∈.
Harold J. Kushner, G. George Yin
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