Signals, Systems & Inference
Par : ,Formats :
- Paiement en ligne :
- Livraison à domicile ou en point Mondial Relay indisponible
- Retrait Click and Collect en magasin gratuit
- Réservation en ligne avec paiement en magasin :
- Indisponible pour réserver et payer en magasin
- Nombre de pages578
- PrésentationRelié
- FormatGrand Format
- Poids0.96 kg
- Dimensions18,4 cm × 24,0 cm × 2,2 cm
- ISBN978-0-13-394328-3
- EAN9780133943283
- Date de parution11/04/2015
- ÉditeurPearson
Résumé
This text combines and extends basic material on the time- and frequency-domain analysis of signals and systems and on pro in ways that are relevant and even essential in many areas of and the applied sciences — signal processing, control, commune financial engineering, biomedicine, and many others. Properties and representations of deterministic signals and systems are elaborated on, including group delay and the structure and behavior of state-space models.
The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection.
The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection.
This text combines and extends basic material on the time- and frequency-domain analysis of signals and systems and on pro in ways that are relevant and even essential in many areas of and the applied sciences — signal processing, control, commune financial engineering, biomedicine, and many others. Properties and representations of deterministic signals and systems are elaborated on, including group delay and the structure and behavior of state-space models.
The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection.
The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection.