Modelling and quantitative methods in fisheries / / by Malcolm Haddon

• Record Nr.: UNINA9910460146103321
• Autore: Haddon Malcolm
• Pubbl/distr/stampa: Boca Raton, FL : , : Chapman and Hall/CRC, an imprint of Taylor and Francis, , 2011
• ISBN: 0-429-10949-0; 1-4398-9417-5; 1-4398-8104-9
• Edizione: [Second edition]
• Descrizione fisica: 1 online resource (435 pages) : illustrations
• Collana: Chapman & Hall book Modelling and quantitative methods in fisheries
• Disciplina: 333.95611015118
• Soggetti: Fisheries - Mathematical models; Electronic books
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index
• Nota di contenuto: Preface to the Second Edition; Preface to the First Edition; Chapter 1. Fisheries and Modelling; Chapter 2. Simple Population Models; Chapter 3. Model Parameter Estimation; Chapter 4. Computer-Intensive Methods; Chapter 5. Randomization Tests; Chapter 6. Statistical Bootstrap Methods; Chapter 7. Monte Carlo Modelling; Chapter 8. Characterization of Uncertainty; Chapter 9. Growth of Individuals; Chapter 10. Stock Recruitment Relationships; Chapter 11. Surplus Production Models; Chapter 12. Age-Structured Models; Chapter 13. Size-Based Models; Appendix A: The Use of Excel in FisheriesBibliography; Back Cover
• Sommario/riassunto: With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries’ scientists and ecologists. By following the examples using Excel, readers see the nuts and bolts of how the methods work and better understand the underlying principles. Excel workbooks are available for download from CRC Press website.

Detection, estimation, and modulation theory . Part III Rasar-sonor signal processing and Gaussian signals in noise / / Harry L. Van Trees

• Record Nr.: UNINA9911019970903321
• Autore: Van Trees Harry L
• Pubbl/distr/stampa: New York, : Wiley, 2001
• ISBN: 9786610541850; 9781280541858; 1280541857; 9780470346655; 0470346655; 9780471463818; 0471463817; 9780471221098; 0471221090; 9781601195579; 1601195575
• Descrizione fisica: 1 online resource (647 p.)
• Disciplina: 621.381536
• Soggetti: Signal theory (Telecommunication); Modulation (Electronics); Estimation theory
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and indexes.
• Nota di contenuto: Contents; 1 Introduction; 1.1 Review of Parts I and II; 1.2 Random Signals in Noise; 1.3 Signal Processing in Radar-Sonar Systems; References; 2 Detection of Gaussian Signals in White Gaussian Noise; 2.1 Optimum Receivers; 2.1.1 Canonical Realization No. 1: Estimator-Correlator; 2.1.2 Canonical Realization No. 2: Filter-Correlator Receiver; 2.1.3 Canonical Realization No. 3: Filter-Squarer-Integrator (FSI) Receiver; 2.1.4 Canonical Realization No. 4: Optimum Realizable Filter Receiver; 2.1.5 Canonical Realization No. 4S: State-variable Realization; 2.1.6 Summary: Receiver Structures; 2.2 Performance2.2.1 Closed-form Expression for μ(s); 2.2.2 ; Approximate Error Expressions; 2.2.3 An Alternative Expression for μ[sub(R)](S); 2.2.4 Performance for a Typical System; 2.3 Summary: Simple Binary Detection; 2.4 Problems; References; 3 General Binary Detection: Gaussian Processes; 3.1 Model and Problem Classification; 3.2 Receiver Structures; 3.2.1 Whitening Approach; 3.2.2 Various Implementations of the Likelihood Ratio Test; 3.2.3 Summary: Receiver Structures; 3.3 Performance; 3.4 Four Special Situations; 3.4.1 Binary Symmetric Case; 3.4.2 Non-zero Means; 3.4.3 Stationary ""Carrier-symmetric"" Bandpass Problems3.4.4 Error Probability for the Binary Symmetric Bandpass Problem; 3.5 General Binary Case: White Noise Not Necessarily Present: Singular Tests; 3.5.1 Receiver Derivation; 3.5.2 Performance: General Binary Case; 3.5.3 Singularity; 3.6 Summary: General Binary Problem; 3.7 Problems; References; 4 Special Categories of Detection Problems; 4.1 Stationary Processes: Long Observation Time; 4.1.1 Simple Binary Problem; 4.1.2 General Binary Problem; 4.1.3 Summary: SPLOT Problem; 4.2 Separable Kernels; 4.2.1 Separable Kernel Model; 4.2.2 Time Diversity4.2.3 Frequency Diversity; 4.2.4 Summary: Separable Kernels; 4.3 Low-Energy-Coherence (LEC) Case; 4.4 Summary; 4.5 Problems; References; 5 Discussion: Detection of Gaussian Signals; 5.1 Related Topics; 5.1.1 M-ary Detection: Gaussian Signals in Noise; 5.1.2 Suboptimum Receivers; 5.1.3 Adaptive Receivers; 5.1.4 Non-Gaussian Processes; 5.1.5 Vector Gaussian Processes; 5.2 Summary of Detection Theory; 5.3 Problems; References; 6 Estimation of the Parameters of a Random Process; 6.1 Parameter Estimation Model; 6.2 Estimator Structure; 6.2.1 Derivation of the Likelihood Function6.2.2 Maximum Likelihood and Maximum A-Posteriori Probability Equations; 6.3 Performance Analysis; 6.3.1 A Lower Bound on the Variance; 6.3.2 Calculation of J[sup(2)](A); 6.3.3 Lower Bound on the Mean-Square Error; 6.3.4 Improved Performance Bounds; 6.4 Summary; 6.5 Problems; References; 7 Special Categories of Estimation Problems; 7.1 Stationary Processes: Long Observation Time; 7.1.1 General Results; 7.1.2 Performance of Truncated Estimates; 7.1.3 Suboptimum Receivers; 7.1.4 Summary; 7.2 Finite-State Processes; 7.3 Separable Kernels; 7.4 Low-Energy-Coherence Case
• Sommario/riassunto: Paperback reprint of one of the most respected classics in the history of engineering publicationTogether with the reprint of Part I and the new Part IV, this will be the most complete treatment of the subject availableProvides a highly-readable discussion of Signal Processing and NoiseFeatures numerous problems and illustrations to help promote understanding of the topicsContents are highly applicable to current systems