Non-Linear Signal Processing
ISTE Ltd and John Wiley & Sons Inc (Verlag)
978-1-84821-456-9 (ISBN)
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1. Basic classification of Non Linear (NL) representations ofsignals: with or without memory 1.1 Memoryless systems effects on signals: Probability Densitytransformations. Random Processes Moment transformations: Pricetheorem and its generalizations. 1.2 Time Dependent NL signal models: integral and differentialequations (Fredholm, Volterra, etc.). 2. Modeling Non-Linear systems 2.1 Hammerstein separable Models 2.2 Cellular networks: Neural Networks, Support VectorMachines 2.3 State Space Equation based: Extended Kalman Filter 3. Parameter estimation in NL systems 3.1 Known Input Methods: Kalman, Least Squares and RecursiveLeast Squares, Supervised (i.e. 'with learning phase'): NeuralNetworks 3.2 Self-learning mode: Kohonen-like algorithms 4. Selected application examples derived from: 4.1 Basic Signal Processing: Polynomial NL systems,hard-limiters, clippers, etc. 4.2 Space Telecommunications: Satellite On-board Solid StatePower Amplifier, Non-Linear Channel Equalizers.
| Erscheint lt. Verlag | 4.8.2016 |
|---|---|
| Reihe/Serie | FOCUS Series |
| Verlagsort | London |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| ISBN-10 | 1-84821-456-1 / 1848214561 |
| ISBN-13 | 978-1-84821-456-9 / 9781848214569 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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