Search results for: pp.1544%E2%80%931548.%0D%0A%5B2%5D%09Xia
2 The Influence of Torquato Tasso's Poetry on Monteverdi's Madrigals
Authors: Christian Giddings
Abstract:
Using rhetorical analysis, this paper analyzes thirteen madrigalian settings of Torquato Tasso's (1544-1595) poetry by Claudio Monteverdi (1567-1643) published between 1587 (Book One) and 1619 (Book Seven). Such analysis suggests that the composer consistently responded to the expressivity and increased formal freedom typical of Tasso's poetry by making greater use of musico-rhetorical figures, as described by the German theorist Joachim Burmeister (1564-1629) in his treatise Musica poetica (1606). The use of rhetorical analysis when examining the influence of the poet Tasso on Monteverdi can illustrate the influence of literary components on music. One cannot overestimate the importance of these texts and their influence on composers of the day. The evidence presented in this paper strongly suggests that exposure to the poems of Torquato Tasso early in his career encouraged Claudio Monteverdi to increasingly adopt a more rhetorical approach in his madrigal compositions.Keywords: Claudio Monteverdi, musico-rhetorical analysis, renaissance, torquato tasso
Procedia PDF Downloads 1521 Solving the Quadratic Programming Problem Using a Recurrent Neural Network
Authors: A. A. Behroozpoor, M. M. Mazarei
Abstract:
In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.
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