Homeric effects in vergil`s narrative, Barchiesi, Alessandro
Старое издание
Автор: Barchiesi Alessandro Название: Homeric Effects in Vergil`s Narrative ISBN: 069116181X ISBN-13(EAN): 9780691161815 Издательство: Wiley Цена: 4528 р. Наличие на складе: Есть у поставщикаПоставка под заказ. Описание:
The study of Homeric imitations in Vergil has one of the longest traditions in Western culture, starting from the very moment the Aeneid was circulated. Homeric Effects in Vergil's Narrative is the first English translation of one of the most important and influential modern studies in this tradition. In this revised and expanded edition, Alessandro Barchiesi advances innovative approaches even as he recuperates significant earlier interpretations, from Servius to G. N. Knauer.
Approaching Homeric allusions in the Aeneid as "narrative effects" rather than glimpses of the creative mind of the author at work, Homeric Effects in Vergil's Narrative demonstrates how these allusions generate hesitations and questions, as well as insights and guidance, and how they participate in the creation of narrative meaning. The book also examines how layers of competing interpretations in Homer are relevant to the Aeneid, revealing again the richness of the Homeric tradition as a component of meaning in the Aeneid. Finally, Homeric Effects in Vergil's Narrative goes beyond previous studies of the Aeneid by distinguishing between two forms of Homeric intertextuality: reusing a text as an individual model or as a generic matrix.
For this edition, a new chapter has been added, and in a new afterword the author puts the book in the context of changes in the study of Latin literature and intertextuality.
A masterful work of classical scholarship, Homeric Effects in Vergil's Narrative also has valuable insights for the wider study of imitation, allusion, intertextuality, epic, and literary theory.
Автор: Barchiesi Franco Название: Precarious Liberation ISBN: 1438436106 ISBN-13(EAN): 9781438436104 Издательство: Неизвестно Цена: 5268 р. Наличие на складе: Невозможна поставка.
Описание: Millions of black South African workers struggled against apartheid to redeem employment and production from a history of abuse, insecurity, and racial despotism. Almost two decades later, however, the prospects of a dignified life of wage-earning work remain unattainable for most South Africans. Through extensive archival and ethnographic research, Franco Barchiesi documents and interrogates this important dilemma in the country's democratic transition: economic participation has gained centrality in the government's definition of virtuous citizenship, and yet for most workers, employment remains an elusive and insecure experience. In a context of market liberalization and persistent social and racial inequalities, as jobs in South Africa become increasingly flexible, fragmented, and unprotected, they depart from the promise of work with dignity and citizenship rights that once inspired opposition to apartheid. Barchiesi traces how the employment crisis and the responses of workers to it challenge the state's normative imagination of work, and raise decisive questions for the social foundations and prospects of South Africa's democratic experiment.
Автор: Daniele Barchiesi Название: Dictionary Learning with Applications to Audio Signals ISBN: 3639666089 ISBN-13(EAN): 9783639666083 Издательство: LAP LAMBERT Academic Publishing Рейтинг: Цена: 16134 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Over-complete transforms have recently become the focus of a wide wealth of research in signal processing, machine learning, statistics and related fields. Their great modelling flexibility allows to find sparse representations and approximations of data that in turn prove to be very efficient in a wide range of applications. Sparse models express signals as linear combinations of a few basis functions called atoms taken from a so-called dictionary. Finding the optimal dictionary from a set of training signals of a given class is the objective of dictionary learning and the main focus of this thesis. The experimental evidence presented here focuses on the processing of audio signals, and the role of sparse algorithms in audio applications is accordingly highlighted.
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