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Two-dimensional signal analysis / / edited by René Garello
| Two-dimensional signal analysis / / edited by René Garello |
| Pubbl/distr/stampa | London, : ISTE, [2008] |
| Descrizione fisica | 1 online resource (312 pages) |
| Disciplina |
621.382/23
621.38223 |
| Altri autori (Persone) | GarelloRené |
| Collana | ISTE |
| Soggetto topico |
Signal theory (Telecommunication)
System analysis |
| ISBN |
9780470611067 (electronic book)
1-282-16496-1 9786612164965 0-470-61106-5 0-470-39364-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Two-Dimensional Signal Analysis; Table of Contents; Introduction; Chapter 1. Basic Elements of 2-D Signal Processing; 1.1. Introduction; 1.2. Deterministic 2-D signals; 1.2.1. Definition; 1.2.2. Particular 2-D signals; 1.3. Random 2-D signals; 1.3.1. Definition; 1.3.2. Characterization up to the second order; 1.3.3. Stationarity; 1.3.4. Characterization of orders higher than two; 1.3.5. Ergodicity; 1.3.6. Specificities of random 2-D signals; 1.3.7. Particular random signals; 1.3.7.1. White noise; 1.3.7.2. Gaussian process; 1.4. 2-D systems; 1.4.1. Definition; 1.4.2. Main 2-D operators
1.4.3. Main properties1.4.4. Linear time-invariant (LTI) system; 1.4.5. Example; 1.4.6. Separable system; 1.4.7. Stability of 2-D systems; 1.4.8. Support of the impulse response - causality; 1.5. Characterization of 2-D signals and systems; 1.5.1. Frequency response of an LTI system; 1.5.2. 2-D Fourier transform; 1.5.2.1. Definition; 1.5.2.2. Properties; 1.5.3. Discrete 2-D Fourier transform; 1.5.3.1. Definition; 1.5.3.2. Properties; 1.5.3.3. Calculation of the 2-D DFT; 1.5.4. 2-D z transform; 1.5.4.1. Definition; 1.5.4.2. Region of convergence; 1.5.4.3. Properties 1.5.4.4. Transfer function of a 2-D system1.5.4.5. 2-D inverse ZT; 1.5.4.6. Application to the study of stability of LTI systems; 1.5.4.7. Minimum or non-minimum phase LTI system; 1.5.5. Frequency characterization of a random 2-D signal.; 1.5.6. Output of a 2-D system with random input; 1.6. 2-D Wold decomposition; 1.6.1. Innovation, determinism and regularity in the 2-D case; 1.6.2. Total decomposition of three fields; 1.6.3. Example of an outcome; 1.7. Conclusion; 1.8. Bibliography; Chapter 2. 2-D Linear Stochastic Modeling; 2.1. Introduction; 2.2. 2-D ARMA models; 2.2.1. Definition 2.2.2. 2-D ARMA models and prediction supports2.2.2.1. Causal models; 2.2.2.2. Causal quarter plane model; 2.2.2.3. Causal model whose support is delimited by any two NSHPs; 2.2.2.4. Semi-causal model; 2.2.2.5. Non-causal model; 2.3. L-Markovian fields; 2.3.1. 2-D Markov fields and L-Markovian fields; 2.3.2. 2-D L-Markovian fields and Gibbs fields; 2.4. "Global" estimation methods; 2.4.1. Maximum likelihood; 2.4.1.1. Estimation criteria by supposing the fixed order; 2.4.1.2. Probability criteria "penalized" to estimate the order of the model; 2.4.2. Yule-Walker equations 2.4.2.1. Representation of minimum variance and formulation2.4.2.2. Non-causal support and L-Markovian fields; 2.4.2.3. Causal support and 2-D AR model; 2.4.2.4. Extension to the 2-D AR non-causal model; 2.4.2.5. Extension to the 2-D ARMA model; 2.4.3. 2-D Levinson algorithm (for the parametric 2-D AR estimation); 2.4.3.1. Recalling the 1-D case; 2.4.3.2. Approach for 2-D causal and non-causal prediction models; 2.4.3.3. Multichannel approach and 2-D QP AR model; 2.4.3.4. Other approaches; 2.5. "Adaptive" or "recursive" estimation methods 2.5.1. Connectivity hypotheses for adaptive or recursive algorithms |
| Record Nr. | UNINA-9910139508403321 |
| London, : ISTE, [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Two-dimensional signal analysis / / edited by René Garello
| Two-dimensional signal analysis / / edited by René Garello |
| Pubbl/distr/stampa | London, : ISTE, [2008] |
| Descrizione fisica | 1 online resource (312 pages) |
| Disciplina |
621.382/23
621.38223 |
| Altri autori (Persone) | GarelloRené |
| Collana | ISTE |
| Soggetto topico |
Signal theory (Telecommunication)
System analysis |
| ISBN |
9780470611067 (electronic book)
1-282-16496-1 9786612164965 0-470-61106-5 0-470-39364-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Two-Dimensional Signal Analysis; Table of Contents; Introduction; Chapter 1. Basic Elements of 2-D Signal Processing; 1.1. Introduction; 1.2. Deterministic 2-D signals; 1.2.1. Definition; 1.2.2. Particular 2-D signals; 1.3. Random 2-D signals; 1.3.1. Definition; 1.3.2. Characterization up to the second order; 1.3.3. Stationarity; 1.3.4. Characterization of orders higher than two; 1.3.5. Ergodicity; 1.3.6. Specificities of random 2-D signals; 1.3.7. Particular random signals; 1.3.7.1. White noise; 1.3.7.2. Gaussian process; 1.4. 2-D systems; 1.4.1. Definition; 1.4.2. Main 2-D operators
1.4.3. Main properties1.4.4. Linear time-invariant (LTI) system; 1.4.5. Example; 1.4.6. Separable system; 1.4.7. Stability of 2-D systems; 1.4.8. Support of the impulse response - causality; 1.5. Characterization of 2-D signals and systems; 1.5.1. Frequency response of an LTI system; 1.5.2. 2-D Fourier transform; 1.5.2.1. Definition; 1.5.2.2. Properties; 1.5.3. Discrete 2-D Fourier transform; 1.5.3.1. Definition; 1.5.3.2. Properties; 1.5.3.3. Calculation of the 2-D DFT; 1.5.4. 2-D z transform; 1.5.4.1. Definition; 1.5.4.2. Region of convergence; 1.5.4.3. Properties 1.5.4.4. Transfer function of a 2-D system1.5.4.5. 2-D inverse ZT; 1.5.4.6. Application to the study of stability of LTI systems; 1.5.4.7. Minimum or non-minimum phase LTI system; 1.5.5. Frequency characterization of a random 2-D signal.; 1.5.6. Output of a 2-D system with random input; 1.6. 2-D Wold decomposition; 1.6.1. Innovation, determinism and regularity in the 2-D case; 1.6.2. Total decomposition of three fields; 1.6.3. Example of an outcome; 1.7. Conclusion; 1.8. Bibliography; Chapter 2. 2-D Linear Stochastic Modeling; 2.1. Introduction; 2.2. 2-D ARMA models; 2.2.1. Definition 2.2.2. 2-D ARMA models and prediction supports2.2.2.1. Causal models; 2.2.2.2. Causal quarter plane model; 2.2.2.3. Causal model whose support is delimited by any two NSHPs; 2.2.2.4. Semi-causal model; 2.2.2.5. Non-causal model; 2.3. L-Markovian fields; 2.3.1. 2-D Markov fields and L-Markovian fields; 2.3.2. 2-D L-Markovian fields and Gibbs fields; 2.4. "Global" estimation methods; 2.4.1. Maximum likelihood; 2.4.1.1. Estimation criteria by supposing the fixed order; 2.4.1.2. Probability criteria "penalized" to estimate the order of the model; 2.4.2. Yule-Walker equations 2.4.2.1. Representation of minimum variance and formulation2.4.2.2. Non-causal support and L-Markovian fields; 2.4.2.3. Causal support and 2-D AR model; 2.4.2.4. Extension to the 2-D AR non-causal model; 2.4.2.5. Extension to the 2-D ARMA model; 2.4.3. 2-D Levinson algorithm (for the parametric 2-D AR estimation); 2.4.3.1. Recalling the 1-D case; 2.4.3.2. Approach for 2-D causal and non-causal prediction models; 2.4.3.3. Multichannel approach and 2-D QP AR model; 2.4.3.4. Other approaches; 2.5. "Adaptive" or "recursive" estimation methods 2.5.1. Connectivity hypotheses for adaptive or recursive algorithms |
| Record Nr. | UNISA-996208334303316 |
| London, : ISTE, [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Two-dimensional signal analysis / / edited by René Garello
| Two-dimensional signal analysis / / edited by René Garello |
| Pubbl/distr/stampa | London, : ISTE, [2008] |
| Descrizione fisica | 1 online resource (312 pages) |
| Disciplina |
621.382/23
621.38223 |
| Altri autori (Persone) | GarelloRené |
| Collana | ISTE |
| Soggetto topico |
Signal theory (Telecommunication)
System analysis |
| ISBN |
9780470611067 (electronic book)
1-282-16496-1 9786612164965 0-470-61106-5 0-470-39364-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Two-Dimensional Signal Analysis; Table of Contents; Introduction; Chapter 1. Basic Elements of 2-D Signal Processing; 1.1. Introduction; 1.2. Deterministic 2-D signals; 1.2.1. Definition; 1.2.2. Particular 2-D signals; 1.3. Random 2-D signals; 1.3.1. Definition; 1.3.2. Characterization up to the second order; 1.3.3. Stationarity; 1.3.4. Characterization of orders higher than two; 1.3.5. Ergodicity; 1.3.6. Specificities of random 2-D signals; 1.3.7. Particular random signals; 1.3.7.1. White noise; 1.3.7.2. Gaussian process; 1.4. 2-D systems; 1.4.1. Definition; 1.4.2. Main 2-D operators
1.4.3. Main properties1.4.4. Linear time-invariant (LTI) system; 1.4.5. Example; 1.4.6. Separable system; 1.4.7. Stability of 2-D systems; 1.4.8. Support of the impulse response - causality; 1.5. Characterization of 2-D signals and systems; 1.5.1. Frequency response of an LTI system; 1.5.2. 2-D Fourier transform; 1.5.2.1. Definition; 1.5.2.2. Properties; 1.5.3. Discrete 2-D Fourier transform; 1.5.3.1. Definition; 1.5.3.2. Properties; 1.5.3.3. Calculation of the 2-D DFT; 1.5.4. 2-D z transform; 1.5.4.1. Definition; 1.5.4.2. Region of convergence; 1.5.4.3. Properties 1.5.4.4. Transfer function of a 2-D system1.5.4.5. 2-D inverse ZT; 1.5.4.6. Application to the study of stability of LTI systems; 1.5.4.7. Minimum or non-minimum phase LTI system; 1.5.5. Frequency characterization of a random 2-D signal.; 1.5.6. Output of a 2-D system with random input; 1.6. 2-D Wold decomposition; 1.6.1. Innovation, determinism and regularity in the 2-D case; 1.6.2. Total decomposition of three fields; 1.6.3. Example of an outcome; 1.7. Conclusion; 1.8. Bibliography; Chapter 2. 2-D Linear Stochastic Modeling; 2.1. Introduction; 2.2. 2-D ARMA models; 2.2.1. Definition 2.2.2. 2-D ARMA models and prediction supports2.2.2.1. Causal models; 2.2.2.2. Causal quarter plane model; 2.2.2.3. Causal model whose support is delimited by any two NSHPs; 2.2.2.4. Semi-causal model; 2.2.2.5. Non-causal model; 2.3. L-Markovian fields; 2.3.1. 2-D Markov fields and L-Markovian fields; 2.3.2. 2-D L-Markovian fields and Gibbs fields; 2.4. "Global" estimation methods; 2.4.1. Maximum likelihood; 2.4.1.1. Estimation criteria by supposing the fixed order; 2.4.1.2. Probability criteria "penalized" to estimate the order of the model; 2.4.2. Yule-Walker equations 2.4.2.1. Representation of minimum variance and formulation2.4.2.2. Non-causal support and L-Markovian fields; 2.4.2.3. Causal support and 2-D AR model; 2.4.2.4. Extension to the 2-D AR non-causal model; 2.4.2.5. Extension to the 2-D ARMA model; 2.4.3. 2-D Levinson algorithm (for the parametric 2-D AR estimation); 2.4.3.1. Recalling the 1-D case; 2.4.3.2. Approach for 2-D causal and non-causal prediction models; 2.4.3.3. Multichannel approach and 2-D QP AR model; 2.4.3.4. Other approaches; 2.5. "Adaptive" or "recursive" estimation methods 2.5.1. Connectivity hypotheses for adaptive or recursive algorithms |
| Record Nr. | UNINA-9910830952203321 |
| London, : ISTE, [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||