Pubbl/distr/stampa	Chichester : J. Wiley & Sons, c1980
Descrizione fisica	xix, 524 p. ; 25 cm
Disciplina	510
Altri autori (Persone)	Ledermann, Walter Vajda, Steven
Collana	Handbook of applicable mathematics ; 1
Soggetto topico	Game theory Group theory - Textbooks Integer programming Linear algebra - Textbooks Linear programming Multilinear algebra - Textbooks Number theory - Textbooks
ISBN	0471277045
Classificazione	AMS 00A20 AMS 11-01 AMS 15-01 AMS 20-01 AMS 90C05 AMS 90C10 AMS 90D
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNISALENTO-991000651689707536

Autore	Kolman Bernard
Edizione	[2nd ed.]
Pubbl/distr/stampa	San Diego, California ; ; London, England : , : Academic Press, , 1995
Descrizione fisica	1 online resource (474 p.)
Disciplina	519.7/2
Collana	Computer Science and Scientific Computing
Soggetto topico	Linear programming
Soggetto genere / forma	Electronic books.
ISBN	0-08-053079-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Front Cover; Elementary Linear Programming with Applications; Copyright Page; Dedication; Table of Contents; Preface; Acknowledgments; Prologue; Chapter 0. Review of Linear Algebra (Optional); 0.1 Matrices; 0.2 Gauss-Jordan Reduction; 0.3 The Inverse of a Matrix; 0.4 Subspaces; 0.5 Linear Independence and Basis; Further Reading; Chapter 1. Introduction to Linear Programming; 1.1 The Linear Programming Problem; 1.2 Matrix Notation; 1.3 Geometry of Linear Programming Problems; 1.4 The Extreme Point Theorem; 1.5 Basic Solutions; Further Reading; Chapter 2. The Simplex Method 2.1 The Simplex Method for Problems in Standard Form2.2 Degeneracy and Cycling (Optional); 2.3 Artificial Variables; Further Reading; Chapter 3. Further Topics in Linear Programming; 3.1 Duality; 3.2 The Duality Theorem; 3.3 Computational Relations between the Primal and Dual Problems; 3.4 The Dual Simplex Method; 3.5 The Revised Simplex Method; 3.6 Sensitivity Analysis; 3.7 Computer Aspects (Optional); Further Reading; Chapter 4. Integer Programming; 4.1 Examples; 4.2 Cutting Plane Methods; 4.3 Branch and Bound Methods; 4.4 Computer Aspects (Optional); Further Reading Chapter 5. Special Types of Linear Programming Problems5.1 The Transportation Problem; 5.2 The Assignment Problem; 5.3 Graphs and Networks: Basic Definitions; 5.4 The Maximal Flow Problem; 5.5 The Shortest Route Problem; 5.6 The Critical Path Method; 5.7 Computer Aspects (Optional); APPENDIX A: Karmarkar's Algorithm; APPENDIX B: Microcomputer Software; APPENDIX C: SMPX; Answers to Odd-Numbered Exercises; Index
Record Nr.	UNINA-9910480893603321

Autore	Kolman, Bernard
Edizione	[2nd ed.]
Pubbl/distr/stampa	San Diego : Academic Press, c1995
Descrizione fisica	xxii, 449 p. : ill. ; 24 cm. + 1 computer disk (3 1/2 in.)
Disciplina	519.72
Altri autori (Persone)	Beck, Robert Edward
Collana	Computer science and scientific computing
Soggetto topico	Linear programming
ISBN	9780124179103 012417910X
Formato	Risorse elettroniche
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNISALENTO-991003273579707536

Autore	Challa Sudha <1953->
Pubbl/distr/stampa	Cambridge : , : Cambridge University Press, , 2011
Descrizione fisica	1 online resource (xii, 375 pages) : digital, PDF file(s)
Disciplina	519.7
Soggetto topico	Linear programming Programming (Mathematics)
ISBN	1-280-88667-6 1-139-00985-0 9786613727985 1-139-00823-4 1-139-01037-9 1-139-00932-X 0-511-97583-X
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover; FUNDAMENTALS OF OBJECT TRACKING; Title; Copyright; Contents; Preface; 1: Introduction to object tracking; 1.1 Overview of object tracking problems; 1.1.1 Air space monitoring; 1.1.2 Video surveillance; 1.1.3 Weather monitoring; 1.1.4 Cell biology; 1.2 Bayesian reasoning with application to object tracking; 1.2.1 Bayes' theorem; 1.2.2 Application to object tracking; 1.3 Recursive Bayesian solution for object tracking; 1.3.1 The generalized object dynamics equation; 1.3.2 The generalized sensor measurement equation; 1.3.3 Generalized object state prediction and conditional densities 1.3.4 Generalized object state prediction and update1.3.5 Generalized object state filtering; 1.3.6 Generalized object state estimates; 1.4 Summary; 2: Filtering theory and non-maneuvering object tracking; 2.1 The optimal Bayesian filter; 2.1.1 Object dynamics and sensor measurement equations; 2.1.2 The optimal non-maneuvering object tracking filter recursion; 2.2 The Kalman filter; 2.2.1 Derivation of the Kalman filter; 2.2.2 The Kalman filter equations; 2.3 The extended Kalman filter; 2.3.1 Linear filter approximations; 2.3.2 The extended Kalman filter equations 2.4 The unscented Kalman filter2.4.1 The unscented transformation; 2.4.2 The unscented Kalman filter algorithm; 2.5 The point mass filter; 2.5.1 Transition and prediction densities; 2.5.2 The likelihood function and normalization factor; 2.5.3 Conditional density; 2.5.4 The point mass filter equations; 2.6 The particle filter; 2.6.1 The particle filter for single-object tracking; 2.6.2 The OID-PF for single-object tracking; 2.6.3 Auxiliary bootstrap filter for single-object tracking; 2.6.4 Extended Kalman auxiliary particle filter for single-object tracking; 2.7 Performance bounds 2.8 Illustrative exampleAngle tracking; 2.9 Summary; 3: Maneuvering object tracking; 3.1 Modeling for maneuvering object tracking; 3.1.1 Single model via state augmentation; 3.1.2 Multiple-model-based approaches; 3.2 The optimal Bayesian filter; 3.2.1 Process, measurement and noise models; 3.2.2 The conditional density and the conditional model probability; 3.2.3 Optimal estimation; 3.3 Generalized pseudo-Bayesian filters; 3.3.1 Generalized pseudo-Bayesian filter of order 1; 3.3.2 Generalized pseudo-Bayesian filter of order 2; 3.4 Interacting multiple model filter 3.4.1 The IMM filter equations3.5 Particle filters for maneuvering object tracking; 3.5.1 Bootstrap filter for maneuvering object tracking; 3.5.2 Auxiliary bootstrap filter for maneuvering object tracking; 3.5.3 Extended Kalman auxiliary particle filter for maneuvering object tracking; 3.6 Performance bounds; 3.7 Illustrative example; 3.8 Summary; 4: Single-object tracking in clutter; 4.1 The optimal Bayesian filter; 4.1.1 Object dynamics, sensor measurement and noise models; 4.1.2 Conditional density; 4.1.3 Optimal estimation; 4.2 The nearest neighbor filter 4.2.1 The nearest neighbor filter equations
Record Nr.	UNINA-9910457534403321

Autore	Pop Petrica C.
Pubbl/distr/stampa	Berlin ; ; Boston : , : De Gruyter, , [2012]
Descrizione fisica	1 online resource (216 p.)
Disciplina	519.64
Collana	De Gruyter Series in Discrete Mathematics and Applications
Soggetto topico	Computer networks -- Design and construction -- Mathematical models Linear programming Combinatorial optimization - Design and construction - Mathematical models Computer networks
Soggetto genere / forma	Electronic books.
ISBN	1-283-85668-9 3-11-026768-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Front matter -- Contents -- Chapter 1. Introduction -- Chapter 2. The Generalized Minimum Spanning Tree Problem (GMSTP) -- Chapter 3. The Generalized Traveling Salesman Problem (GTSP) -- Chapter 4. The Railway Traveling Salesman Problem (RTSP) -- Chapter 5. The Generalized Vehicle Routing Problem (GVRP) -- Chapter 6. The Generalized Fixed-Charge Network Design Problem (GFCNDP) -- Chapter 7. The Generalized Minimum Edge-Biconnected Network Problem (GMEBCNP) -- Bibliography -- Index
Record Nr.	UNINA-9910462642403321