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1. |
Record Nr. |
UNINA9910480214303321 |
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Autore |
Olshevsky Vadim |
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Titolo |
Structured Matrices in Mathematics, Computer Science, and Engineering [[electronic resource]] |
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Pubbl/distr/stampa |
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Providence, : American Mathematical Society, 2001 |
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ISBN |
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0-8218-7871-9 |
0-8218-2092-3 |
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Descrizione fisica |
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1 online resource (362 p.) |
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Collana |
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Contemporary Mathematics ; ; v.281 |
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Disciplina |
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Soggetti |
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Matrices -- Congresses |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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""Contents""; ""Foreword""; ""Part V. Fast Algorithms""; ""The Schur algorithm for matrices with Hessenberg displacement structure""; ""Fast inversion algorithms for a class of block structured matrices""; ""A fast and stable solver for recursively semi-separable systems of linear equations""; ""Part VI. Numerical Issues""; ""Stability properties of several variants of the unitary Hessenberg QR algorithm""; ""Comparison of algorithms for Toeplitz least squares and symmetric positive definite linear systems""; ""Stability of Toeplitz matrix inversion formulas"" |
""Necessary and sufficient conditions for accurate and efficient rational function evaluation and factorizations of rational matrices""""Updating and downdating of orthonormal polynomial vectors and some applications""; ""Rank-revealing decompositions of symmetric Toeplitz matrices""; ""Part VII. Iterative Methods. Preconditioners""; ""A survey of preconditioners for ill-conditioned Toeplitz systems""; ""Preconditioning of Hermitian block�Toeplitz�Toeplitz�block matrices by level�1 preconditioners""; ""Part VIII. Linear Algebra and Various Applications"" |
""A generalization of the Perron-Frobenius theorem for non-linear perturbations of Stiltjes matrices""""The rhombus matrix: Definition and properties"" |
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2. |
Record Nr. |
UNINA9910367566503321 |
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Autore |
Eriksson Sandra |
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Titolo |
Permanent Magnet Synchronous Machines / Sandra Eriksson |
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Pubbl/distr/stampa |
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
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Basel, Switzerland : , : MDPI, , 2019 |
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ISBN |
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Descrizione fisica |
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1 electronic resource (282 p.) |
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Soggetti |
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History of engineering and technology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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Interest in permanent magnet synchronous machines (PMSMs) is continuously increasing worldwide, especially with the increased use of renewable energy and the electrification of transports. This book contains the successful submissions of fifteen papers to a Special Issue of Energies on the subject area of "Permanent Magnet Synchronous Machines". The focus is on permanent magnet synchronous machines and the electrical systems they are connected to. The presented work represents a wide range of areas. Studies of control systems, both for permanent magnet synchronous machines and for brushless DC motors, are presented and experimentally verified. Design studies of generators for wind power, wave power and hydro power are presented. Finite element method simulations and analytical design methods are used. The presented studies represent several of the different research fields on permanent magnet machines and electric drives. |
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3. |
Record Nr. |
UNINA9910674044803321 |
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Autore |
Castellano Giovanna |
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Titolo |
Computational Intelligence in Healthcare |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (226 p.) |
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Soggetti |
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Information technology industries |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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The number of patient health data has been estimated to have reached 2314 exabytes by 2020. Traditional data analysis techniques are unsuitable to extract useful information from such a vast quantity of data. Thus, intelligent data analysis methods combining human expertise and computational models for accurate and in-depth data analysis are necessary. The technological revolution and medical advances made by combining vast quantities of available data, cloud computing services, and AI-based solutions can provide expert insight and analysis on a mass scale and at a relatively low cost. Computational intelligence (CI) methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods, have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. CI-based systems can learn from data and evolve according to changes in the environments by taking into account the uncertainty characterizing health data, including omics data, clinical data, sensor, and imaging data. The use of CI in healthcare can improve the processing of such data to develop intelligent solutions for prevention, diagnosis, treatment, and follow-up, as well as for the analysis of administrative processes. The present Special Issue on computational intelligence for healthcare is intended to show the potential and the practical impacts of CI techniques in challenging healthcare applications. |
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