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Advances in Computational Collective Intelligence : 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30 - December 3, 2020, Proceedings / / Marcin Hernes, Krystian Wojtkiewicz, Edward Szczerbicki (edsitors)
| Advances in Computational Collective Intelligence : 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30 - December 3, 2020, Proceedings / / Marcin Hernes, Krystian Wojtkiewicz, Edward Szczerbicki (edsitors) |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XXIX, 823 p. 348 illus., 240 illus. in color.) |
| Disciplina | 006.33 |
| Collana | Communications in computer and information science |
| Soggetto topico |
Expert systems (Computer science)
Artificial intelligence Intelligent agents (Computer software) Semantic Web Human-computer interaction |
| ISBN | 3-030-63119-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Data Mining and Machine Learning -- Deep Learning and Applications for Industry 4.0 -- Recommender Systems -- Computer Vision Techniques -- Decision Support and Control Systems -- Intelligent Management Information Systems -- Innovations in Intelligent Systems -- Intelligent Modeling and Simulation Approaches for Games and Real World Systems -- Experience Enhanced Intelligence to IoT -- Data Driven IoT for Smart Society -- Applications of Collective Intelligence -- Natural Language Processing -- Low Resource Languages Processing -- Computational Collective Intelligence and Natural Language Processing. |
| Record Nr. | UNINA-9910427697403321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in computational collective intelligence : 13th international, conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Krystian Wojtkiewicz [and three others]
| Advances in computational collective intelligence : 13th international, conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Krystian Wojtkiewicz [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (742 pages) |
| Disciplina | 006.33 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Expert systems (Computer science)
Intelligent agents (Computer software) |
| ISBN | 3-030-88113-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464513903316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in computational collective intelligence : 13th international, conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Krystian Wojtkiewicz [and three others]
| Advances in computational collective intelligence : 13th international, conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Krystian Wojtkiewicz [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (742 pages) |
| Disciplina | 006.33 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Expert systems (Computer science)
Intelligent agents (Computer software) |
| ISBN | 3-030-88113-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910502981303321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Information Systems, Artificial Intelligence and Knowledge Management [[electronic resource] ] : 6th International Conference on Information and Knowledge Systems, ICIKS 2023, Portsmouth, UK, June 22–23, 2023, Proceedings / / edited by Inès Saad, Camille Rosenthal-Sabroux, Faiez Gargouri, Salem Chakhar, Nigel Williams, Ella Haig
| Advances in Information Systems, Artificial Intelligence and Knowledge Management [[electronic resource] ] : 6th International Conference on Information and Knowledge Systems, ICIKS 2023, Portsmouth, UK, June 22–23, 2023, Proceedings / / edited by Inès Saad, Camille Rosenthal-Sabroux, Faiez Gargouri, Salem Chakhar, Nigel Williams, Ella Haig |
| Autore | Saad Inès |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 005.3 |
| Altri autori (Persone) |
Rosenthal-SabrouxCamille
GargouriFaiez ChakharSalem WilliamsNigel HaigElla |
| Collana | Lecture Notes in Business Information Processing |
| Soggetto topico |
Application software
Expert systems (Computer science) Machine learning Computer and Information Systems Applications Knowledge Based Systems Machine Learning |
| ISBN | 3-031-51664-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Decision Making, Recommender Systems, and Information Support Systems -- Models-simulators in business decision-making processes for pharmaceutical enterprises -- Decision and Information Support System to implement the Framework of Twelve steps for building decision models -- Graph Representation Learning for Recommendation Systems: A short review -- FITradeoff Decision Support System applied to solve a Supplier Selection Problem -- A Step-by-Step Decision Process to Support Application Migration to the Cloud-Native Architecture -- Information Systems and Machine Learning -- ACTIVE SMOTE for Imbalanced Medical Data Classification -- Evolutionary Graph-Clustering vs Evolutionary Cluster-Detection Approaches for Community Identification in PPI Networks -- Predictive monitoring of business process execution delays -- An accurate Random Forest-based Action Recognition Technique using only velocity and landmarks’ distances -- Efficient topic Detection using an Adaptive Neural Network architecture -- Exploiting Machine Learning Technique for attack detection in Intrusion Detection System (IDS) based on Protocol -- Robust Aggregation Function in Federated Learning -- Knowledge Management, Context and Ontology -- Should I Share or Should I Go? A Study of Tacit Knowledge Sharing Behaviors in Extended Enterprises -- Designing a User Contextual Profile Ontology: A Focus on the Vehicle Sales Domain -- Management of Implicit Ontology Changes Generated by Non-conservative JSON Instance Updates in the τJOWL Environment -- A Model Driven Architecture approach for implementing sensitive business processes -- Extension of the functional dimension of BPMN based on MDA approach for sensitive business processes execution -- Inclusive Mobile Health System for Yoruba Race in Nigeria -- Cybersecurity and Intelligent Systems -- Epistemology for Cyber Security: A Controlled Natural Language Approach -- Application of fuzzy decision support systems in IT industry functioning -- Moving towards explainable AI using Fuzzy Networks in decision making process -- Natural Language Processing for Decision Systems -- Sentiment Analysis: Effect of Combining BERT as an Embedding Technique with CNN Model for Tunisian Dialect -- An Enhanced Machine Learning-Based Analysis of Teaching and Learning Process for Higher Education System -- Topic Modelling of Legal Texts using bidirectional encoder representations from Sentence Transformers. |
| Record Nr. | UNINA-9910805579703321 |
Saad Inès
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNINA-9910484403103321 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNISA-996465748403316 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in knowledge representation / / edited by Carlos Ramirez
| Advances in knowledge representation / / edited by Carlos Ramirez |
| Pubbl/distr/stampa | Rijeka, Croatia : , : IntechOpen, , [2012] |
| Descrizione fisica | 1 online resource (286 pages) : illustrations |
| Disciplina | 006.332 |
| Soggetto topico |
Expert systems (Computer science)
Artificial intelligence Knowledge representation (Information theory) |
| ISBN | 953-51-5634-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910138268103321 |
| Rijeka, Croatia : , : IntechOpen, , [2012] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910460377903321 |
|
Mahler Ronald P. S.
|
||
| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910797934303321 |
|
Mahler Ronald P. S.
|
||
| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910816058003321 |
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Mahler Ronald P. S.
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| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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