Wavelet networks
Q. Zhang low, Albert Benveniste
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Citation edge evidence
- Nonlinear black-box modeling in system identification: a unified overview→Wavelet networksLegacy edge — source detail unavailable
- Neural networks for classification: a survey→Wavelet networksLegacy edge — source detail unavailable
- Wavelet networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Wavelet networks→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Wavelet networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Wavelet networks→Universal approximation bounds for superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Wavelet networks→Theory of the backpropagation neural networkLegacy edge — source detail unavailable
- Theory of the backpropagation neural network→Multilayer feedforward networks are universal approximatorsLegacy 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
- Nonlinear black-box modeling in system identification: a unified overview→Universal approximation bounds for superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Approximation by superpositions of a sigmoidal function→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Neural networks for classification: a survey→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Neural networks for classification: a survey→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Neural networks for classification: a survey→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Multilayer feedforward networks are universal approximators→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Multilayer feedforward networks are universal approximators→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
- Universal approximation bounds for superpositions of a sigmoidal function→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
- Universal approximation bounds for superpositions of a sigmoidal function→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Nonlinear black-box modeling in system identification: a unified overview | 1995 | 1,930 |
| Neural networks for classification: a survey | 2000 | 1,672 |
Links
Topics
| Neural Networks and Applications | Computer Science |
| Image and Signal Denoising Methods | Computer Science |
| Blind Source Separation Techniques | Computer Science |
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