Flaubert's straight and suspect saints [[electronic resource] ] : the unity of Trois contes / / Aimée Israel-Pelletier

• Record Nr.: UNINA9910457807803321
• Autore: Israel-Pelletier Aimée
• Pubbl/distr/stampa: Amsterdam ; ; Philadelphia, : John Benjamins Pub. Co., 1991
• ISBN: 1-283-35864-6; 9786613358646; 90-272-7775-3
• Descrizione fisica: 1 online resource (178 p.)
• Collana: Purdue University monographs in Romance languages, , 0165-8743 ; ; v. 36
• Disciplina: 843/.8
• Soggetti: Narration (Rhetoric) - History - 19th century; 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 (p. [151]-161) and index.
• Nota di contenuto: FLAUBERT'S STRAIGHT AND SUSPECT SAINTS; Editorial page; Title page; Copyright page; Dedication; Table of contents; Acknowledgments; Introduction: Meaning and Character in Flaubert; 1. The Trois contes; 2. The Women of Pont-l'Evêqueque: A Subversive Sorority; 3. Murdering the Father: Re-writing the Legend of Saint Julien l'Hospitalier; 4. Reading the Landscape of Desire and Writing; Conclusion: Straight and Suspect Texts: A Poetics of Transgression; Notes; Bibliography and Selected Works on Trois contes; Index
• Sommario/riassunto: Israel Pelletier argues that Trois contes demands a different kind of reading which distinguishes it from Madame Bovary and other Flaubert texts. By the time he wrote this late work, Flaubert's attitude toward his characters and the role of fiction had changed to accommodate different social, political, and literary pressures. He constructed two opposing levels of meaning for each of the stories, straight and ironic, which produced a more fruitful way of addressing some of his concerns and assumptions about language and illusion. Included in this study are a provocative feminist

Sequential methods in pattern recognition and machine learning [[electronic resource] /] / K.S. Fu

• Record Nr.: UNINA9910778600003321
• Autore: Fu K. S (King Sun), <1930-1985.>
• Pubbl/distr/stampa: New York, : Academic Press, 1968
• ISBN: 1-282-29019-3; 9786612290190; 0-08-095559-2
• Descrizione fisica: 1 online resource (245 p.)
• Collana: Mathematics in science and engineering ; ; v. 52
• Disciplina: 001.5/3
• Soggetti: Perceptrons; Statistical decision; Machine learning
• 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: Front Cover; Sequential Methods in Pattern Recognition and Machine Learning; Copyright Page; Contents; Preface; Chapter 1. Introduction; 1.1 Pattern Recognition; 1.2 Deterministic Classification Techniques; 1.3 Training in Linear Classifiers; 1.4 Statistical Classification Techniques; 1.5 Sequential Decision Model for Pattern Classification; 1.6 Learning in Sequential Pattern Recognition Systems; 1.7 Summary and Further Remarks; References; Chapter 2. Feature Selection and Feature Ordering; 2.1 Feature Selection and Ordering-Information Theoretic Approach; 2.2 Feature Selection and Ordering-Karhunen-Loève Expansion2.3 Illustrative Examples; 2.4 Summary and Further Remarks; References; Chapter 3. Forward Procedure for Finite Sequential Classification Using Modified Sequential Probability Ratio Test; 3.1 Introduction; 3.2 Modified Sequential Probability Ratio Test-Discrete Case; 3.3 Modified Sequential Probability Ratio Test-Continuous Case; 3.4 Procedure of Modified Generalized Sequential Probability Ratio Test; 3.5 Experiments in Pattern Classification; 3.6 Summary and Further Remarks; References; Chapter 4. Backward Procedure for Finite Sequential Recognition Using Dynamic Programming4.1 Introduction; 4.2 Mathematical Formulation ; and Basic Functional Equation; 4.3 Reduction of Dimensionality; 4.4 Experiments in Pattern Classification; 4.5 Backward Procedure for Both Feature Ordering and Pattern Classification; 4.6 Experiments in Feature Ordering and Pattern Classification; 4.7 Use of Dynamic Programming for Feature-Subset Selection; 4.8 Suboptimal Sequential Pattern Recognition; 4.9 Summary and Further Remarks; References; Chapter 5. Nonparametric Procedure in Sequential Pattern Classification5.1 Introduction; 5.2 Sequential Ranks and Sequential Ranking Procedure; 5.3 A Sequential Two-Sample Test Problem; 5.4 Nonparametric Design of Sequential Pattern Classifiers; 5.5 Analysis of Optimal Performance and a Multiclass Generalization; 5.6 Experimental Results and Discussions; 5.7 Summary and Further Remarks; References; Chapter 6. Bayesian Learning in Sequential Pattern Recognition Systems; 6.1 Supervised Learning Using Bayesian Estimation Techniques; 6.2 Nonsupervised Learning Using Bayesian Estimation Techniques; 6.3 Bayesian Learning of Slowly Varying Patterns6.4 Learning of Parameters Using an Empirical Bayes Approach; 6.5 A General Model for Bayesian Learning Systems; 6.6 Summary and Further Remarks; References; Chapter 7. Learning in Sequential Recognition Systems Using Stochastic Approximation; 7.1 Supervised Learning Using Stochastic Approximation; 7.2 Nonsupervised Learning Using Stochastic Approximation; 7.3 A General Formulation of Nonsupervised Learning Systems Using Stochastic Approximation; 7.4 Learning of Slowly Time-Varying Parameters Using Dynamic Stochastic Approximation; 7.5 Summary and Further Remarks
• Sommario/riassunto: Sequential methods in pattern recognition and machine learning