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[null,"1.","Record Nr.",null,"UNISA996386788003316"]
[null,null,"Titolo",null,"A Serious and faithfull representation of the judgments of ministers of the Gospel within the the province of London [[electronic resource] ] : contained in a letter from the to the general and his councell of war / / delivered to His Excellence by some of the subscribers, Ian. 18, 1649"]
[null,null,"Pubbl/distr/stampa",null,"[Edinburgh], : Printed at London, and re-printed at Edinburgh by Evan Tyler ..., 1649"]
[null,null,"Descrizione fisica",null,"[2], 14 p"]
[null,null,"Soggetti",null,"Church and state - England"]
[{"$nulls":4},"Great Britain History Civil War, 1642-1649"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Contains on p. 13-14 a list of 47 subscribers to the \"Representation\", headed by Thomas Gataker."]
[{"$nulls":4},"Reproduction of original in the Union Theological Seminary Library, New York."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,null,"Sommario/riassunto","eebo-0160"]
[null,"2.","Record Nr.",null,"UNINA9910299714603321"]
[null,null,"Autore",null,"Kiranyaz Serkan"]
[null,null,"Titolo",null,"Multidimensional particle swarm optimization for machine learning and pattern recognition / / Serkan Kiranyaz, Turker Ince, Moncef Gabbouj"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Springer, 2013"]
[null,null,"ISBN",null,"3-642-37846-3"]
[null,null,"Edizione",null,"[1st ed. 2014.]"]
[null,null,"Descrizione fisica",null,"1 online resource (xxviii, 321 pages) : illustrations (some color)"]
[null,null,"Collana",null,"Adaptation, learning, and optimization ; ; 15"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Particles - Optical properties"]
[{"$nulls":4},"Optical pattern recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"ISSN: 1867-4534.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Chap. 1 Introduction -- Chap. 2 Optimization Techniques -- Chap. 3 Particle Swarm Optimization -- Chap. 4 Multidimensional Particle Swarm Optimization -- Chap. 5 Improving Global Convergence -- Chap. 6 Dynamic Data Clustering -- Chap. 7 Evolutionary Artificial Neural Networks -- Chap. 8 Personalized ECG Classification -- Chap. 9 Image Classification Through a Collective Network of Binary Classifiers -- Chap. 10 Evolutionary Feature Synthesis for Image Retrieval."]
[null,null,null,"Sommario/riassunto","For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach.   After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets.   The book will be of benefit to researchers and practitioners "]
[{"$nulls":4},"working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications."]