زبان‌شناسی جبری؛ مدل‌های تحلیلی اثر سلیمان مارکوس

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering Content: Edited by Pages ii-iii Edited by Page v Copyright page Page vi Preface Pages vii-viii Solomon Marcus Chapter I Languages and Partitions Pages 1-35 Chapter II Linguistic Typology Pages 36-80 Chapter III Parts of Speech and Syntactic Types Pages 81-114 Chapter IV Grammatical Gender Pages 115-155 Chapter V Configurations Pages 156-199 Chapter VI Subordination and Projectivity Pages 200-246 Author Index Pages 247-249 Subject Index Pages 250-254 Studies theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. This title considers many computing techniques, such as methods of operator approximation with any given accuracy; methods of covariance matrix estimation; and, methods for low-rank matrix approximations.