202 research outputs found
The "Six Characters" of Giuseppe Fava's Delirio (1980)
No full textCare lettrici & Cari lettori,
we are thrilled to present you with Volume 36 of PSA - The Journal oh the Pirandello Society of America. This year's issue features a striking cover image of a scene from A Green Vein of Madness, a theatrical adaptation of Alessio Arena's acclaimed 2020 book, "La vena verde". Similarly engaging with Pirandello's legacy, Pierlorenzo Randazzo's "The Six Characters of Giuseppe Fava's Delirio (1980)" offers a detailed comparative analysis of Fava's play "Delirio" and Luigi Pirandello's "Six Characters in Search of an Author" (1921). Randazzo explores how Fava reimagines Pirandello's work in a farcical light, employing this reinterpretation to highlight Pirandello's metatheatrical techniques, which serve as a metaphor for the crisis of human identity. While both plays address themes of lost identity, Delirio sets itself apart by depicting its characters as concrete, earthly beings, as opposed to the more abstract and conceptual characters found in Pirandello's original work
Optimization of difference patterns for monopulse antennas by a hybrid real/integer-coded differential evolution method
No full textOptimization of the difference patterns for monopulse antennas by a hybrid real/integer-coded differential evolution method
Author(s): Caorsi, S (Caorsi, S); Massa, A (Massa, A); Pastorino, M (Pastorino, M); Randazzo, A (Randazzo, A)
Source: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION Volume: 53 Issue: 1 Pages: 372-376 DOI: 10.1109/TAP.2004.838788 Part: Part 2 Published: JAN 2005
Times Cited: 46 (from Web of Science)
Cited References: 9 [ view related records ] Citation Map
Abstract: The optimization of difference patterns of monopulse antennas is considered. The synthesis problem is recast as an optimization problem by defining a suitable cost function. In particular, in this paper, the cost function is based on constraints on the side-lobe levels. A subarray configuration is adopted and the excitations of the difference pattern are approximately determined. The optimization problem isefficiently solved by a differential evolution algorithm, which is able to contemporarily handle real and integer unknowns. Numerical results are reported concerning classical array configurations previously considered in the literature.
Accession Number: WOS:000226261600014
Document Type: Article
Language: English
Author Keywords: array antennas; evolutionary algorithm; monopulse antennas; sum and difference patterns
KeyWords Plus: SUM; ARRAYS
Reprint Address: Caorsi, S (reprint author), Univ Pavia, Dept Elect, Via Palestro 3, I-27100 Pavia, Italy
Addresses:
1. Univ Pavia, Dept Elect, I-27100 Pavia, Italy
E-mail Address: [email protected]
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Web of Science Category: Engineering, Electrical & Electronic; Telecommunications
Subject Category: Engineering; Telecommunications
IDS Number: 886VT
ISSN: 0018-926
Quantitative Inversion of Multiantenna Ground-Penetrating Radar Data with Modeling Error Correction Based on Long Short-Term Memory Cells
No full textQuantitative inversion of GPR data opens the door to precise characterization of underground environments. However, in order to make the inverse scattering problem solution easier from a computational viewpoint, simplifying assumptions are often applied, i.e., two-dimensional approximations or the consideration of idealized field probes and electromagnetic sources. These assumptions usually produce modeling errors, which can degrade the dielectric reconstruction results considerably. In this article, a processing step based on long short-term memory cells is proposed for the first time to correct the modeling error in a multiantenna GPR setting. In particular, time-domain GPR data are fed into a neural network trained with couples of finite-difference time-domain simulations, where a set of sample targets are simulated in both realistic and idealized configurations. Once trained, the neural network outputs an approximation of multiantenna GPR data as they are collected by an ideal two-dimensional measurement setup. The inversion of the processed data is then accomplished by means of a regularizing Newton-based nonlinear scheme with variable exponent Lebesgue space formulation. A numerical study has been conducted to assess the capabilities of the proposed inversion methodology. The results indicate the possibility of effectively compensating for modeling error in the considered test cases
RNN-based multistatic scattered-field processing for the solution of electromagnetic imaging problems in multilayer environments
No full textA Hybrid Qualitative-Quantitative Electromagnetic Imaging Method for Subsurface Prospecting
No full textIn the present paper, a hybrid electromagnetic imaging method for subsurface prospection is presented. The approach is based on the cascade of two blocks: a time-domain qualitative reconstruction algorithm followed by a multifrequency quantitative inverse-scattering technique. In the first phase, the scattered-field data estimated by adaptive filtering are exploited by a beamforming method to produce an initial image of buried targets. In the second phase, a multifrequency inexact-Newton inversion approach developed in Lebesgue spaces with variable exponents uses the first-step image in two different qualitative-quantitative combination strategies: as a priori information for setting the exponent function and to weight the solution updates inside the iterative inversion procedure. The approach has been validated using numerically simulated scattered-field data. An analysis on the effects of the application of the two qualitative-quantitative combination strategies is presented
FE-Based Microwave Inverse Scattering in Nonconstant-Exponent Spaces: A Numerical Assessment
No full textThe development of microwave-based inverse scattering techniques to inspect bodies and structures in a noninvasive way has inspired numerous applications [1] , [2] , which range from biomedical diagnostics to industrial settings and geophysics [3]. In all these promising fields, a successful implementation of microwave inverse scattering methods is founded on a couple of main ingredients, namely, a correct modeling of the electromagnetic problem along with the measurement configuration, and a proper inversion procedure capable of retrieving an accurate estimation of targets' properties
Nonlinear Inverse-Scattering in Variable-Exponent Spaces for Multifrequency Subsurface Imaging
No full textIn this paper, a subsurface imaging configuration is considered, with the goal of retrieving the quantitative dielectric properties of buried targets from scattered electric field measurements performed by a set of antennas above the soil. The acquired scattered-field data are processed by a nonlinear inverse-scattering approach in variable-exponent Lebesgue spaces able to jointly exploit multifrequency data, which is extended here for the first time to subsurface imaging problems. Numerical simulations are presented as a preliminary assessment of the proposed inverse-scattering technique, where a multistatic ground penetrating radar configuration is adopted
Inversion of ground penetrating radar data in nonconstant-exponent Lebesgue spaces
No full textGround Penetrating Radar (GPR) is a non-invasive imaging technique widely adopted in subsurface prospection,
e.g., for soil mapping, demining, utility detection, road pavement monitoring, etc. The output of GPR systems is usually
provided as a B-scan, i.e., a two-dimensional plot of the received electromagnetic signal versus time. However, such a
representation is usually difficult to interpret and requires skilled users. A significant enhancement could be obtained by
applying inverse-scattering techniques, which are in principle able to directly provide an image of the dielectric properties of
the inspected region. In this contribution, a novel inversion procedure is presented. It is based on an outer-inner inexactNewton scheme, in which the linear problem obtained at each Newton step is solved by using a Landweber-like procedure
performing a regularization in the framework of the variable-exponent Lebesgue spaces . The exponent function is
adaptively built during iterations by exploiting the currently retrieved solution. In particular, low values of are assigned to
the background, in order to enhance the sparsity of the solution in this region, whereas values close to 2 are used inside
targets. The developed approach allows obtaining better results than the corresponding Hilbert-space method. Moreover, it
allows avoiding the manual selection of the exponent parameter, which is the main drawback of fixed-exponent Lebesguespace techniques
Quantitative imaging of buried targets through a variable-exponent finite-element approach
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