Model-based signal processing James V. Candy.
Series: Adaptive and learning systems for signal processing, communications, and controlPublisher: Hoboken, N.J. : IEEE Press : Wiley-Interscience, c2006Description: xxi, 677 p. : ill. ; 25 cmISBN: 0471236322Other title: Model-based signal processing [electronic resource]Subject(s): Signal processing -- Digital techniquesOnline resources: Click here to access online Review: "Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing." "The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems."--BK JACKET.| Item type | Current location | Home library | Collection | Shelving location | Call number | Status | Date due | Barcode | Item holds |
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Central Library (CL) | Central Library (CL) | NFIC | General Stacks | 621.3822 CAN (Browse shelf) | Available | SEECS007448 |
Browsing Central Library (CL) shelves, Shelving location: General Stacks Close shelf browser
| 621.3822 BAR Signal detection and estimation | 621.3822 BIL Digital alias-free signal processing | 621.3822 BYR Signal processing : a mathematical approach | 621.3822 CAN Model-based signal processing | 621.3822 CAR Telecommunications topics : applications of functions and probabilities in electronic communications | 621.3822 CAS Multiuser detection in CDMA mobile terminals | 621.3822 CAV Digital signal processing |
"Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing." "The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems."--BK JACKET.

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