Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.

This book presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise case-based reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications.

Cognition and artificial intelligence are entering a new era in which the aspects of symbolic manipulation and of connectionism begin to come together. This leads to a dialog of truly interdisciplinary character. The book covers aspects of fuzzy logic, case based reasoning, learning as well as meaning, language, and consciousness. The authors of this topical volume have their background in logic, computer science, physics and mathematics, philosophy, psychology and neurobiology.

This book constitutes the refereed proceedings of the 7th International Conference on Case-Based Reasoning, ICCBR 2007, held in Belfast, Northern Ireland, UK in August 2007.

The 15 revised full research papers and 18 revised poster papers presented together with 3 invited talks were carefully reviewed and selected from 64 submissions. The papers address all current aspects of case-based reasoning and feature original theoretical research, applied research, and deployed applications with practical, social, environmental or economic significance.

Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.

This volume contains all the papers presented at the Ninth International Con- rence on Algorithmic Learning Theory (ALT'98), held at the European education centre Europ]aisches Bildungszentrum (ebz) Otzenhausen, Germany, October 8{ 10, 1998. The Conference was sponsored by the Japanese Society for Arti cial Intelligence (JSAI) and the University of Kaiserslautern. Thirty-four papers on all aspects of algorithmic learning theory and related areas were submitted, all electronically. Twenty-six papers were accepted by the program committee based on originality, quality, and relevance to the theory of machine learning. Additionally, three invited talks presented by Akira Maruoka of Tohoku University, Arun Sharma of the University of New South Wales, and Stefan Wrobel from GMD, respectively, were featured at the conference. We would like to express our sincere gratitude to our invited speakers for sharing with us their insights on new and exciting developments in their areas of research. This conference is the ninth in a series of annual meetings established in 1990. The ALT series focuses on all areas related to algorithmic learning theory including (but not limited to): the theory of machine learning, the design and analysis of learning algorithms, computational logic of/for machine discovery, inductive inference of recursive functions and recursively enumerable languages, learning via queries, learning by arti cial and biological neural networks, pattern recognition, learning by analogy, statistical learning, Bayesian/MDL estimation, inductive logic programming, robotics, application of learning to databases, and gene analyses."

Cognition and artificial intelligence are entering a new era in which the aspects of symbolic manipulation and of connectionism begin to come together. This leads to a dialog of truly interdisciplinary character. The book covers aspects of fuzzy logic, case based reasoning, learning as well as meaning, language, and consciousness. The authors of this topical volume have their background in logic, computer science, physics and mathematics, philosophy, psychology and neurobiology.

This volume presents a selection of 42 refereed and revised contributions (includ- ing some invited lectures) which were presented at the 17th Annual Conference of the "Gesellschaft fur Klassifikation e. V." (GfKl), the German Classification Society. This conference was held at the University of Kaiserslautern from March 3 - 5, 1993 and jointly hosted by the Research Center for Mathematical Logic of the Heidelberg Academy for the Humanities and Sciences, the University of Kaiserslautern, and the German Research Center for Artificial Intelligence (DFKI GmbH). The local orga- nization was performed by Michael M. Richter, Wolfgang Lenski, Sabine Friedrich, Annette Klein, and Elisabeth Wette-Roch of the Computer Science Department of the University of Kaiserslautern and the Research Center for Mathematical Logic of the Heidelberg Academy for the Humanities and Sciences, respectively. The mem- bers of the Scientific Program Committee were Hans-Hermann Bock, PaulO. Degens, Matthias Herfurth, Hans-Joachim Hermes, Rudiger Klar, Rudolf Mathar, Michael M. Richter, and Rudolf Wille.

This volume presents the proceedings of the Computer Science Logic Workshop CSL '92, held in Pisa, Italy, in September/October 1992. CSL '92 was the sixth of the series and the first one held as Annual Conference of the European Association for Computer Science Logic (EACSL). Full versions of the workshop contributions were collected after their presentation and reviewed. On the basis of 58 reviews, 26 papers were selected for publication, and appear here in revised final form. Topics covered in the volume include: Turing machines, linear logic, logic of proofs, optimization problems, lambda calculus, fixpoint logic, NP-completeness, resolution, transition system semantics, higher order partial functions, evolving algebras, functional logic programming, inductive definability, semantics of C, classes for a functional language, NP-optimization problems, theory of types and names, sconing and relators, 3-satisfiability, Kleene's slash, negation-complete logic programs, polynomial-time oracle machines, and monadic second-order properties.

This volume presents the proceedings of the workshop CSL '91 (Computer Science Logic) held at the University of Berne, Switzerland, October 7-11, 1991. This was the fifth in a series of annual workshops on computer sciencelogic (the first four are recorded in LNCS volumes 329, 385, 440, and 533). The volume contains 33 invited and selected papers on a variety of logical topics in computer science, including abstract datatypes, bounded theories, complexity results, cut elimination, denotational semantics, infinitary queries, Kleene algebra with recursion, minimal proofs, normal forms in infinite-valued logic, ordinal processes, persistent Petri nets, plausibility logic, program synthesis systems, quantifier hierarchies, semantics of modularization, stable logic, term rewriting systems, termination of logic programs, transitive closure logic, variants of resolution, and many others.

This volume presents the proceedings of an international workshop on the processing of declarative knowledge. The workshop was organized and hosted by the German Research Center for Artificial Intelligence (DFKI) in cooperation with the Association for Logic Programming (ALP) and the Gesellschaft f}r Informatik (GI). Knowledge is often represented using definite clauses, rules, constraints, functions, conceptual graphs, and related formalisms. The workshop addressed such high-level representations and their efficient implementation required for declarative knowledge bases. Many of the papers treat representation methods, mainly concept languages, and many treat implementation methods, such as transformation techniques and WAM-like abstract machines. Several papers describe implemented knowledge-processing systems. The competition between procedural and declarative paradigms was discussed in a panel session, and position statements of the panelists are included in the volume.

The workshop Computer Science Logic '90 was held at the Max-Planck-Haus in Heidelberg, Germany, October 1-5, 1990. It was the fourth in a series of worskhops, following CSL '89 at the University of Kaiserslautern (see LNCS 440), CSL '88 at the University of Duisberg (see LNCS 385), and CSL '87 at the University of Karlsruhe (see LNCS 329). This volume contains 24 papers, chosen by means of a review procedure from the 35 papers presented at the workshop, some of which were invited and some selected from a total of 89 submissions. The papers cover a wide range of topics arising from the applications of logic to computer science.

This volume contains the revised versions of 28 papers presented at the third workshop on Computer Science Logic held in Kaiserslautern, FRG, October 2-6, 1989. These proceedings cover a wide range of topics both from theoretical and applied areas of computer science. More specifically, the papers deal with problems arising at the border of logic and computer science, e.g. in complexity, data base theory, logic programming, artificial intelligece, and temporal logic. The volume should be of interest to all logicians and computer scientists working in the above field.

This volume contains the papers which were presented at the second workshop "Computer Science Logic" held in Duisburg, FRG, October 3-7, 1988. These proceedings cover a wide range of topics both from theoretical and applied areas of computer science. More specifically, the papers deal with problems arising at the border of logic and computer science: e.g. in complexity, data base theory, logic programming, artificial intelligence, and concurrency. The volume should be of interest to all logicians and computer scientists working in the above fields.

This volume contains the papers which were presented to the workshop "Computer-Science Logic" held in Karlsruhe on October 12-16, 1987. Traditionally Logic, or more specifically, Mathematical Logic splits into several subareas: Set Theory, Proof Theory, Recursion Theory, and Model Theory. In addition there is what sometimes is called Philosophical Logic which deals with topics like nonclassical logics and which for historical reasons has been developed mainly at philosphical departments rather than at mathematics institutions. Today Computer Science challenges Logic in a new way. The theoretical analysis of problems in Computer Science for intrinsic reasons has pointed back to Logic. A broad class of questions became visible which is of a basically logical nature. These questions are often related to some of the traditional disciplines of Logic but normally without being covered adequately by any of them. The novel and unifying aspect of this new branch of Logic is the algorithmic point of view which is based on experiences people had with computers. The aim of the "Computer-Science Logic" workshop and of this volume is to represent the richness of research activities in this field in the German-speaking countries and to point to their underlying general logical principles.

This book presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise case-based reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications.

Die deutsche FrA1/4hjahrsschule fA1/4r KA1/4nstliche Intelligenz, jAhrlich veranstaltet von der Fachgruppe 1.2 "KA1/4nstliche Intelligenz und Mustererkennung" der Gesellschaft fA1/4r Informatik, ist in den letzten Jahren zu einem festen Begriff geworden. Dieses Buch ist der dritte Band von Kursausarbeitungen vergangener FrA1/4hjahrsschulen, hier aus den Jahren 1985 und 1986. Es vergrAAert die thematische Vielfalt des bereits VerfA1/4gbaren um neuartige EinfA1/4hrungen in LISP und PROLOG, sowie ausfA1/4hrliche BeitrAge A1/4ber Robotik, Programmverifikation, Qualitative Modelle, Kognitive Modelle und Automatisches Beweisen.

Als eigenstandige Disziplin gibt es die Nichtstandard-Analysis etwa seit dem Jahre 1960. Inzwischen hat sie eine sturmische Entwicklung genommen, die sich keineswegs auf die Analysis be- schrankte. Viele bekannte Namen sind mit ihr verbunden, doch erscheint es gerecht, den von Ab aham ob n on besonders her- vorzuheben. Er scheint nicht nur als erster die Moglichkeiten der mathematischen Logik erkannt zu haben, }1odelle der Analysis mit Infinitesimalien zu konstruieren, sondern er hat auch den weiteren Verlauf der Entwicklung in ganz ungewohnlicher Weise beeinfluf5t. Dieses Buch solI den Mathematiker (und nieht primar den Logi- ker) in die Welt der Nichtstandard-Methoden einfuhren. Dabei werden zwei Aspekte unterschieden: Zum einen mochte man wis- sen, wie diese Hethoden arbeiten und zum zweiten mochte man wissen, waJtum man so vorgehen darf. Das "wie" wird erst ein- mal durch die Angabe eines Axiomensystems beschrieben, des sen dUrre Einfachheit im weiteren Verlaufe durch Beispiele und An- wendungen mit Leben erfUllt wird. Das "warum" ist eine Frage der mathematischen Logik; sie wird im letzten Kapitel (IX) diskutiert und beantwortet. Ob und wann man sich hiermit be- schaftigt, ist weitgehend Geschmackssache; urn Nichtstandard- Analysis praktisch zu betreiben, ist die Kenntnis der modell- theoretischen Methoden jedenfalls keine 8edingung (wie man auch nichts von der Konstruktion der reellen Zahlen wissen mue, urn Analysis zu treiben). An Axiomensystemen werden zwei verschiedene vorgestellt: Keis- ler's Axiome fUr die elementare Analysis (Kar. II) und Nelson's Axiome fUr die gesamte Hengenlehre (Kap. IV).

Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.