D-Index & Metrics Best Publications
Electronics and Electrical Engineering
UK
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 76 Citations 27,935 405 World Ranking 178 National Ranking 11
Electronics and Electrical Engineering D-index 78 Citations 28,715 427 World Ranking 304 National Ranking 13

Research.com Recognitions

Awards & Achievements

2023 - Research.com Electronics and Electrical Engineering in United Kingdom Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Nonlinear system

Nonlinear system, Algorithm, System identification, Control theory and Identification are his primary areas of study. His Nonlinear system research includes themes of Nonlinear system identification, Estimation theory, Frequency response, Applied mathematics and Differential equation. His research integrates issues of Artificial neural network, Radial basis function network, Radial basis function and Mathematical optimization in his study of Algorithm.

His study looks at the intersection of System identification and topics like Cluster analysis with Computation, Recursive partitioning and Hybrid algorithm. Stephen A. Billings has researched Control theory in several fields, including Control engineering and Structure. His Identification study incorporates themes from Pseudorandom binary sequence, Piecewise linear model, Selection, Structure and Discrete system.

His most cited work include:

  • Orthogonal least squares methods and their application to non-linear system identification (1328 citations)
  • Input-output parametric models for non-linear systems Part II: stochastic non-linear systems (977 citations)
  • Non-linear system identification using neural networks (814 citations)

What are the main themes of his work throughout his whole career to date?

Stephen A. Billings focuses on Nonlinear system, Control theory, Algorithm, System identification and Identification. His Nonlinear system study combines topics from a wide range of disciplines, such as Frequency response, Frequency domain, Mathematical analysis and Applied mathematics. The Control theory study combines topics in areas such as Function and Structure.

His work carried out in the field of Algorithm brings together such families of science as Artificial neural network, Machine learning, Wavelet and Mathematical optimization. His study looks at the relationship between System identification and fields such as Artificial intelligence, as well as how they intersect with chemical problems. The concepts of his Identification study are interwoven with issues in Selection and Noise.

He most often published in these fields:

  • Nonlinear system (54.14%)
  • Control theory (33.54%)
  • Algorithm (24.44%)

What were the highlights of his more recent work (between 2008-2020)?

  • Nonlinear system (54.14%)
  • Control theory (33.54%)
  • System identification (22.22%)

In recent papers he was focusing on the following fields of study:

His main research concerns Nonlinear system, Control theory, System identification, Frequency domain and Frequency response. His Nonlinear system research incorporates themes from Structural engineering, Mathematical analysis, Applied mathematics and Vibration isolation. In the subject of general Control theory, his work in Nonlinear control is often linked to Harmonics, thereby combining diverse domains of study.

His System identification research integrates issues from Estimation theory, Algorithm, Mathematical optimization, Artificial intelligence and Autoregressive model. Stephen A. Billings interconnects Linear system and Identification in the investigation of issues within Algorithm. His research in Frequency response intersects with topics in Vibration, Electronic engineering and Parametric statistics.

Between 2008 and 2020, his most popular works were:

  • Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains (451 citations)
  • Theoretical study of the effects of nonlinear viscous damping on vibration isolation of sdof systems (107 citations)
  • Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit (83 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Nonlinear system

His primary areas of investigation include Nonlinear system, Control theory, Algorithm, System identification and Frequency response. A large part of his Nonlinear system studies is devoted to Volterra series. His work on Nonlinear control as part of general Control theory research is frequently linked to Harmonics, bridging the gap between disciplines.

His studies deal with areas such as Machine learning, Linear system and Mathematical optimization as well as Algorithm. As a part of the same scientific family, Stephen A. Billings mostly works in the field of Mathematical optimization, focusing on Wavelet transform and, on occasion, Artificial neural network, Network model and Particle swarm optimization. The various areas that Stephen A. Billings examines in his System identification study include Time–frequency analysis, Basis function, Control engineering, Autoregressive model and Artificial intelligence.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Orthogonal least squares methods and their application to non-linear system identification

S. Chen;S. A. Billings;W. Luo.
International Journal of Control (1989)

1970 Citations

Orthogonal least squares methods and their application to non-linear system identification

S. Chen;S. A. Billings;W. Luo.
International Journal of Control (1989)

1970 Citations

Input-output parametric models for non-linear systems Part II: stochastic non-linear systems

I J Leontaritis;S A Billings.
International Journal of Control (1985)

1710 Citations

Input-output parametric models for non-linear systems Part II: stochastic non-linear systems

I J Leontaritis;S A Billings.
International Journal of Control (1985)

1710 Citations

Non-linear system identification using neural networks

S. Chen;S. A. Billings;Peter Grant.
International Journal of Control (1990)

1412 Citations

Non-linear system identification using neural networks

S. Chen;S. A. Billings;Peter Grant.
International Journal of Control (1990)

1412 Citations

Representations of non-linear systems: the NARMAX model

S. Chen;S. A. Billings.
International Journal of Control (1989)

1270 Citations

Representations of non-linear systems: the NARMAX model

S. Chen;S. A. Billings.
International Journal of Control (1989)

1270 Citations

Neural Networks for Nonlinear Dynamic System Modelling and Identification

S. Chen;S. A. Billings.
International Journal of Control (1992)

1017 Citations

Neural Networks for Nonlinear Dynamic System Modelling and Identification

S. Chen;S. A. Billings.
International Journal of Control (1992)

1017 Citations

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