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Parameter Estimation of Hidden Diffusion Processes: Particle Filter vs. Modified Baum-Welch Algorithm

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A. Benabdallah, G. Radons

Data Structures and Algorithms · Submitted 30 Nov 2005

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim It is shown that the modified Baum-Welch algorithm is capable of estimating the system parameters with better accuracy than particle filters.

how it is stated · asserted 0.98 read the record →

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arXiv IDcs/0511108 (version 1)
Pith ID4GLYUNZ2, Pith's permanent record of this paper and its review
CitationA. Benabdallah, G. Radons. "Parameter Estimation of Hidden Diffusion Processes: Particle Filter vs. Modified Baum-Welch Algorithm." arXiv:cs/0511108 (2005). https://pith.science/paper/4GLYUNZ2
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,466 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.67 · randomized assignment 0.01 · states quantitative result 0.04 · compares with prior results 0.97 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We propose a new method for the estimation of parameters of hidden diffusion processes. Based on parametrization of the transition matrix, the Baum-Welch algorithm is improved. The algorithm is compared to the particle filter in application to the noisy periodic systems. It is shown that the modified Baum-Welch algorithm is capable of estimating the system parameters with better accuracy than particle filters.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We propose a new method for the estimation of parameters of hidden diffusion processes. contribution 1.00 0.92 0.04 asserted 0.95
s1 Based on parametrization of the transition matrix, the Baum-Welch algorithm is improved. method 0.84 0.81 0.03 asserted 1.00
s2 The algorithm is compared to the particle filter in application to the noisy periodic systems. method 0.91 0.85 0.03 asserted 0.86
s3 It is shown that the modified Baum-Welch algorithm is capable of estimating the system parameters with better accuracy than particle filters. result 1.00 0.91 0.91 asserted 0.98

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 1.00.

What was examined, and what was not

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not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
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  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We propose a new method for the estimation of parameters of hidden diffusion processes. Based on parametrization of the transition matrix, the Baum-Welch algorithm is improved. The algorithm is compared to the particle filter in application to the noisy periodic systems. It is shown that the modified Baum-Welch algorithm is capable of estimating the system parameters with better accuracy than particle filters.

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