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1. |
Record Nr. |
UNINA9910458421603321 |
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Autore |
Kaplan William <1957-> |
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Titolo |
Canadian maverick : the life and times of Ivan C. Rand / / William Kaplan |
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Pubbl/distr/stampa |
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Toronto, [Ontario] ; ; Buffalo, [New York] ; ; London, [England] : , : Published for the Osgoode Society for Canadian Legal History by University of Toronto Press, , 2009 |
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©2009 |
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ISBN |
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1-4426-8593-X |
1-4426-9762-8 |
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Descrizione fisica |
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1 online resource (547 p.) |
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Collana |
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Osgoode Society for Canadian Legal History |
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Disciplina |
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Soggetti |
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Judges - Canada |
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 bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Frontmatter -- Contents -- Foreword -- Preface -- 1. The Right Start -- 2. The Young Lawyer Tries Politics -- 3. The Railway Counsel at Work and at Home -- 4. The Framework of Freedom -- 5. Rand's Formula -- 6. Rand Tackles the Palestine Problem -- 7. King Coal -- 8. A Founding Dean of Law -- 9. Canadian Gothic Meets the Mambo King -- 10. Rand's Disastrous Investigation into Labour Disputes -- Conclusion -- Notes -- Index |
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Sommario/riassunto |
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In Canadian Maverick, bestselling author William Kaplan critically examines the life and times of lawyer, politician, academic, and Supreme Court Justice Ivan C. Rand. Born to a working-class New Brunswick family, Rand's hard work and impressive intellect led to an extraordinary career that redefined Canada's legal landscape.Rand's 1943 appointment to the Supreme Court of Canada invigorated what was then a pedestrian institution. His work in labour law, including his development of the Rand Formula, and his key judgments in civil liberties cases inspired a generation of Canadian judges, lawyers, and law students.Kaplan's rigorous study encompasses Rand's legal contributions, his pivotal role in the creation of the State of Israel, and his position as founding dean of the University of Western Ontario's |
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Faculty of Law. An absorbing account of a complex and sometimes contradictory figure, Canadian Maverick draws a compelling portrait of one of Canada's most influential legal minds. |
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2. |
Record Nr. |
UNINA9910299717703321 |
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Titolo |
Compressed sensing & sparse filtering / / Avishy Y. Carmi, Lyudmila S. Mihaylova, Simon J. Godsill, editors |
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Pubbl/distr/stampa |
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Heidelberg, Germany : , : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (xii, 502 pages) : illustrations (some color) |
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Collana |
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Signals and Communication Technology, , 1860-4862 |
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Disciplina |
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Soggetti |
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Signal processing - Digital techniques |
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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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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction to Compressed Sensing and Sparse Filtering -- The Geometry of Compressed Sensing -- Sparse Signal Recovery with Exponential-Family Noise -- Nuclear Norm Optimization and its Application to Observation Model Specification -- Nonnegative Tensor Decomposition -- Sub-Nyquist Sampling and Compressed Sensing in Cognitive Radio Networks -- Sparse Nonlinear MIMO Filtering and Identification -- Optimization Viewpoint on Kalman Smoothing with Applications to Robust and Sparse Estimation -- Compressive System Identification -- Distributed Approximation and Tracking using Selective Gossip -- Recursive Reconstruction of Sparse Signal Sequences -- Estimation of Time-Varying Sparse Signals in Sensor Networks -- Sparsity and Compressed Sensing in Mono-static and Multi-static Radar Imaging -- Structured Sparse Bayesian Modelling for Audio Restoration -- Sparse Representations for Speech Recognition. |
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Sommario/riassunto |
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This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon |
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the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related approaches. Each methodology has its own formalities for dealing with such problems. As an example, in the Bayesian approach, sparseness promoting priors such as Laplace and Cauchy are normally used for penalising improbable model variables, thus promoting low complexity solutions. Compressed sensing techniques and homotopy-type solutions, such as the LASSO, utilise l1-norm penalties for obtaining sparse solutions using fewer observations than conventionally needed. The book emphasizes on the role of sparsity as a machinery for promoting low complexity representations and likewise its connections to variable selection and dimensionality reduction in various engineering problems. This book is intended for researchers, academics and practitioners with interest in various aspects and applications of sparse signal processing. . |
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