Kischka, P., University of Jena, Germany Leopold-Wildburger, U., University of Graz, Austria
Mφhring, R.H., Technische Universitat Berlin, Germany Radermacher, F.-J., University of Ulm, Germany (Eds.)
Models, Methods and Decision Support for Management
Essays in Honor of Paul Stahly
2001. X, 417 pp. 57 figs., 35 tabs. Hardcover
3-7908-1373-7
The book presents a broad view on the nature of intelligent decision-making which is characterized
by the use of models and methods in the framework of decision support for management.
Contributions to this volume dedicated to Paul Stahly on the occasion of his 65th birthday include
theoretical research and applications in optimization, operations research as well as decision
support and management systems.
Keywords: Operations Research, Simulation, Optimization, Programming
Fields: Operations Research/Decision Theory
Written for: Researchers in the fields of operations research and management science
Book category: Anniversary Publication
Publication language: English
Kandel, A., University of South Florida, Tampa, FL, USA
Last, M., University of South Florida, Tampa, FL, USA
Bunke, H., University of Bern, Switzerland
(Eds.)
Data Mining and Computational Intelligence
2001. XII, 356 pp. 90 figs., 45 tabs. Hardcover
3-7908-1371-0
The volume offers a comprehensive coverage of the recent advances in the application of soft
computing and fuzzy logic theory to data mining and knowledge discovery databases. It focuses on
some of the hardest, and yet unsolved, issues of data mining like understandability of patterns,
finding complex relationships between attributes, handling missing and noisy data, mining very
large datasets, change detection in time series, and integration of the discovery process with
database management systems.
Keywords: Data mining, knowledge discovery in databases, machine learning, fuzzy logic,
computational intelligence
Contents: Data Mining with Neuro-Fuzzy Models.- Granular Computing in Data Mining.-
Fuzzification and Reduction of Information - Theoretic Rule Sets.- Mining Fuzzy Association Rules
in a Database Containing Relational and Transactional Data.- Fuzzy Linguistics Summaries via
Association Rules.- The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for
Data-Based Generation of Small Interpretable Rule Bases in High-Dimensional Search Spaces.-
Discovering Knowledge from Fuzzy Concept Lattice.- Mining of Labeled Incomplete Data Using
Fast Dimension Partitioning.- Mining a Growing Feature Map by Data Skeleton Modelling.- Soft
Regression - A Data Mining Tool.- Some Practical Applications of Soft Computing and Data
Mining.- Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web
Search.- Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series.
Series: Studies in Fuzziness and Soft Computing.VOL. 68
Lenz, H.-J., Freie Universitat Berlin, Germany
Wilrich, P.-T., Freie Universitat Berlin, Germany
(Eds.)
Frontiers in Statistical Quality Control 6
2001. XII, 375 pp. 88 figs., 49 tabs. Softcover
3-7908-1374-5
The book is a collection of papers presented at the 5th International Workshop on Intelligent
Statistical Quality Control in Wurzburg, Germany.
Contributions deal with methodology and successful industrial applications. They can be grouped in
four catagories: Sampling Inspection, Statistical Process Control, Data Analysis and Process
Capability Studies and Experimental Design.
Keywords: Quality Control, Statistical Quality Control, Sampling Inspection, Statistical Process
Control, Data Analysis, Process Capability Studies, Experimental Design
Fields: Statistics for Business, Economics, Insurance; Operations
Research/Decision Theory
Written for: Researchers in statistics, operations research, business, and
engineering
Book category: Proceedings
Publication language: English
Chaitin, G.J., IBM Research Division, Hawthorne, NY, USA
Exploring RANDOMNESS
2001. X, 164 pp. Hardcover
1-85233-417-7
This essential companion volume to CHAITIN's highly successful books The Unknowable and
The Limits of Mathematics, also published by Springer, presents the technical core of his theory
of program-size complexity, also known as algorithmic information theory. (The two previous
volumes are more concerned with applications to meta-mathematics.) LISP is used to present the
key algorithms and to enable computer users to interact with the author's proofs and discover for
themselves how they work. The LISP code for this book is available at the author's Web site
together with a Java applet LISP interpreter: http://www.cs.auckland.ac.nz/CDMTCS/chaitin/ait/
"No one has looked deeper and farther into the abyss of randomness and its role in mathematics
than Greg Chaitin. This book tells you everything he's seen. Don't miss it."
John Casti, Santa Fe Institute, Author of "Goedel: A Life of Logic"
Contents: Introduction: Historical Introduction. What is LISP? Why do I like it? How to Program
my Universal Turing Machine in LISP.- Program Size: A Self-Delimiting Turing Machine
considered as a Set of (Program, Output) Pairs. How to Construct Self-delimiting Turing Machines:
The Kraft Inequality. The Connection Between Program-Size Complexity and Algorithmic
Probability. The Basic Result on Relative Complexity.- Randomness: Theoretical Interlude - What
is Randomness? My definitions. Proof that Martin-Lφf Randomness is Equivalent to Martin-Lφf
Randomness. Proof that Solovay Randomness is Equivalent to Strong Chaitin Randomness.-
Future Work: Extending AIT to the Size of Programs for Computing Infinite Sets and to
Computations with Oracles. Postscript - Letter to a Young Reader.
Series: Discrete Mathematics and Theoretical Computer Science.
Lange, K., UCLA School of Medicine, Los Angeles, CA, USA
Numerical Analysis for Statisticians
1st ed. 1999. Corr. 2nd printing 2000. XV, 356 pp. 9 figs. Hardcover
0-387-94979-8
This book presents topics in numerical analysis for statisticians. It would be suitable as a text for a
graduate course in statistical computing. The focus is on principles of numerical analysis intended
to equip students to craft their own software and to understand the advantages and disadvantages
of different numerical methods.
Contents: Recurrence Relations.- Power Series Expansions.- Continued Fraction Expansions.-
Asymptotic Expansions.- Solution of Nonlinear Equations.- Vector and Matrix Norms.- Linear
Regression and Matrix Inversion.- Eigenvalues and Eigenvectors.- Splines.- The EM Algorithm.-
Newton's Method and Scoring.- Variations on the EM Theme.- Convergence of Optimization
Algorithms.- Constrained Optimization.- Concrete Hilbert Spaces.- Quadrature Methods.- The
Fourier Transform.- The Finite Fourier Transform.- Wavelets.- Generating Random Deviates.-
Independent Monte Carlo.- Bootstrap Calculations.- Finite-State Markov Chains.- Markov Chain
Monte Carlo.
Series: Statistics and Computing.
Trentelman, H.L., University of Groningen, The Netherlands
Stoorvogel, A.A., Eindhoven University of Technology, Eindhoven, The Netherlands
Hautus, M., Eindhoven University of Technology, Eindhoven, The Netherlands
Control Theory for Linear Systems
2001. XVI, 389 pp. 47 figs. Hardcover
1-85233-316-2
Control Theory for Linear Systems deals with the mathematical theory of feedback control of
linear systems. It treats a wide range of control synthesis problems for linear state space systems
with inputs and outputs. The book provides a treatment of these problems using state space
methods, often with a geometric flavour. Its subject matter ranges from controllability and
observability, stabilization, disturbance decoupling, and tracking and regulation, to linear quadratic
regulation, H2 and H-infinity control, and robust stabilization. Each chapter of the book contains a
series of exercises, intended to increase the reader's understanding of the material. Often, these
exercises generalize and extend the material treated in the regular text.
Contents: Linear Systems: basic theory.- Controllability and observability.- Controlled invariant
subspaces.- Conditioned invariant subspaces.- (C,A,B) pairs and dynamic feedback.- System
zeros and system invertibility.- Tracking and regulation.- The linear quadratic regulator problem.-
The H2 optimal control problem.- H-infinity control and robustness.- The state feedback H-infinity
control problem.- The H-infinity control problem with measurement feedback.