Orthogonal least squares learning algorithm for radial basis function networks
Sheng Chen, C.F.N. Cowan low, P.M. Grant
The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- ANFIS: adaptive-network-based fuzzy inference system→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Fuzzy basis functions, universal approximation, and orthogonal least-squares learning→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Fuzzy logic systems for engineering: a tutorial→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Nonlinear black-box modeling in system identification: a unified overview→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Trends in extreme learning machines: A review→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Neural Network Toolbox™ User's Guide→Orthogonal least squares learning algorithm for radial basis function networksLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→Genetic algorithms in search, optimization, and machine learningLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→Fast Learning in Networks of Locally-Tuned Processing UnitsLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive NetworksLegacy edge — source detail unavailable
- Orthogonal least squares learning algorithm for radial basis function networks→Learning Automata: An IntroductionLegacy edge — source detail unavailable
- ANFIS: adaptive-network-based fuzzy inference system→Fuzzy basis functions, universal approximation, and orthogonal least-squares learningLegacy edge — source detail unavailable
- ANFIS: adaptive-network-based fuzzy inference system→Fast Learning in Networks of Locally-Tuned Processing UnitsLegacy edge — source detail unavailable
- Fuzzy logic systems for engineering: a tutorial→Fuzzy basis functions, universal approximation, and orthogonal least-squares learningLegacy edge — source detail unavailable
- Fuzzy logic systems for engineering: a tutorial→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Fuzzy logic systems for engineering: a tutorial→Fast Learning in Networks of Locally-Tuned Processing UnitsLegacy edge — source detail unavailable
- Nonlinear black-box modeling in system identification: a unified overview→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Fuzzy basis functions, universal approximation, and orthogonal least-squares learning→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Approximation by superpositions of a sigmoidal function→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
Links
Topics
| Neural Networks and Applications | Computer Science |
| Structural Health Monitoring Techniques | Engineering |
| Non-Destructive Testing Techniques | Engineering |
Is this record sound?
complete
Nothing in this record contradicts itself and no field we check is missing.
- supports3 author record(s) attached.
- supports29 reference(s) recorded.
- neutralThe DOI carries no year to check against.
- supportsA title is present.
Provenance
sha256 a08467ae9504f237…