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1. |
Record Nr. |
UNINA9910841872603321 |
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Autore |
Litovski Vanco |
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Titolo |
Lecture Notes in Analog Electronics : Noise in Electronic Circuits and Low Noise Amplifier Design / / by Vančo Litovski |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (217 pages) |
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Collana |
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Lecture Notes in Electrical Engineering, , 1876-1119 ; ; 1122 |
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Disciplina |
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Soggetti |
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Power electronics |
Electronic circuits |
Electronic circuit design |
Power Electronics |
Electronic Circuits and Systems |
Electronics Design and Verification |
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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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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Electronic noise modelling -- Electronic noise analysis in basic circuits -- Low noise amplifiers -- Solved problems -- Spice examples -- Noise measurement. |
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Sommario/riassunto |
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This book discusses unified noise models of the broadest set of electronic components including, resistors, diodes, all types of transistors, and most types of opto-electronic devices. The noise, however, is a phenomenon which is inherent to any technology. It is omnipresent. It is obstructing every application and in many cases special actions must be undertaken to recognize the main function’s signal in the mistiness of the noise. The number of types of noise sources in electronics is almost unlimited. The book offers unique comprehensive approach to noise analysis in electronic circuits based on modified nodal analysis and the superposition theorem. It also encompasses a broadest set of low noise amplifier design procedures covering BJT, MOSET, MESFET, and HEMT technologies. |
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2. |
Record Nr. |
UNINA9910557288403321 |
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Autore |
Moeslund Thomas |
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Titolo |
Statistical Machine Learning for Human Behaviour Analysis |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
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Descrizione fisica |
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1 online resource (300 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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This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field. |
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