Results 1 to 10 of about 124,023 (246)
Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise [PDF]
Complexity, 2018 This paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective in solving nonlinear optimization problem.
Junhong Li, Xiao Li
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Iterative Sparse Identification of Nonlinear Dynamics
IEEE Open Journal of Signal Processing, 2023 Abstract In order to extract governing equations from time-series data, various approaches are proposed. Among those, sparse identification of nonlinear dynamics (SINDy) stands out as a successful method capable of modeling governing equations with a minimal number of terms, utilizing the principles of compressive sensing.
Jinho Choi
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Improving Person Re-Identification With Iterative Impression Aggregation [PDF]
IEEE Transactions on Image Processing, 2020 Our impression about one person often updates after we see more aspects of him/her and this process keeps iterating given more meetings. We formulate such an intuition into the problem of person re-identification (re-ID), where the representation of a query (probe) image is iteratively updated with new information from the candidates in the gallery ...
Dengpan Fu +6 more
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Iterative human and automated identification of wildlife images [PDF]
Nature Machine Intelligence, 2021 This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections.
Zhongqi Miao +5 more
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Biometric identification using local iterated function [PDF]
The European Physical Journal Special Topics, 2014 Biometric identification protocol has been received an increasing interest recently. It is a process that determines person identity by making use of their biometric features. A new biometric identification method is presented in this paper based on partial self-similarity that used to identify features within fingerprint images.
Mohammed G. Al-Saidi, Nadia +1 more
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Iterated diffusion maps for feature identification
Applied and Computational Harmonic Analysis, 2018 Recently, the theory of diffusion maps was extended to a large class of local kernels with exponential decay which were shown to represent various Riemannian geometries on a data set sampled from a manifold embedded in Euclidean space. Moreover, local kernels were used to represent a diffeomorphism, H, between a data set and a feature of interest using
Berry, Tyrus, Harlim, John
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Blind iterative channel identification and equalization [PDF]
ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240), 2002 We propose an iterative solution to the problem of blindly and jointly identifying the channel response and transmitted symbols in a digital communications system. The proposed algorithm iterates between a symbol estimator, which uses tentative channel estimates to provide soft symbol estimates, and a channel estimator, which uses the symbol estimates ...
R.R. Lopes, J.R. Barry
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Iterative LBG clustering for SIMO channel identification
Journal of Communications and Networks, 2003 This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise.
Laddomada, Massimiliano, Daneshgaran, F.
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Iterative time reversal based flaw identification
Computers & Mathematics with Applications, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Seidl, Robert, Rank, Ernst
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Iterative system identification using multigrid techniques
Electronics Letters, 1992 A new system identification algorithm utilizing multigrid techniques is presented. System identification algorithms based on iterative techniques are enhanced and made more efficient using the multigrid methods. The reduction in the number of iterations required to converge to a solution is realised by forcing the low frequency error components to ...
D.A. Richter, M. Tummala
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