Author:
Publisher:
ISBN:
Category : Neural networks (Computer science)
Languages : en
Pages : 608
Book Description
The 1997 IEEE International Conference on Neural Networks, June 9-12, 1997, Westin Galleria Hotel, Houston, Texas, USA.
Author:
Publisher:
ISBN:
Category : Neural networks (Computer science)
Languages : en
Pages : 608
Book Description
Publisher:
ISBN:
Category : Neural networks (Computer science)
Languages : en
Pages : 608
Book Description
The 1997 IEEE International Conference on Neural Networks, June 9-12, 1997, Westin Galleria Hotel, Houston, Texas, USA.
Author: IEEE Neural Networks Council
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN:
Category : Computers
Languages : en
Pages : 684
Book Description
Instrumentation thrusts and achievements are reported in the field of simulation of aerospace dynamics. Quantified mapping techniques and measurements in research in unsteady fluid mechanics phenomena are described and the frontiers of speed and flight simulation are extended."
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN:
Category : Computers
Languages : en
Pages : 684
Book Description
Instrumentation thrusts and achievements are reported in the field of simulation of aerospace dynamics. Quantified mapping techniques and measurements in research in unsteady fluid mechanics phenomena are described and the frontiers of speed and flight simulation are extended."
IEEE ... International Conference on Neural Networks
Author: Shun'ichi Amari
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 608
Book Description
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 608
Book Description
Evolving Connectionist Systems
Author: Nikola Kasabov
Publisher: Springer Science & Business Media
ISBN: 144713740X
Category : Computers
Languages : en
Pages : 308
Book Description
Many methods and models have been proposed for solving difficult problems such as prediction, planning and knowledge discovery in application areas such as bioinformatics, speech and image analysis. Most, however, are designed to deal with static processes which will not change over time. Some processes - such as speech, biological information and brain signals - are not static, however, and in these cases different models need to be used which can trace, and adapt to, the changes in the processes in an incremental, on-line mode, and often in real time. This book presents generic computational models and techniques that can be used for the development of evolving, adaptive modelling systems. The models and techniques used are connectionist-based (as the evolving brain is a highly suitable paradigm) and, where possible, existing connectionist models have been used and extended. The first part of the book covers methods and techniques, and the second focuses on applications in bioinformatics, brain study, speech, image, and multimodal systems. It also includes an extensive bibliography and an extended glossary. Evolving Connectionist Systems is aimed at anyone who is interested in developing adaptive models and systems to solve challenging real world problems in computing science or engineering. It will also be of interest to researchers and students in life sciences who are interested in finding out how information science and intelligent information processing methods can be applied to their domains.
Publisher: Springer Science & Business Media
ISBN: 144713740X
Category : Computers
Languages : en
Pages : 308
Book Description
Many methods and models have been proposed for solving difficult problems such as prediction, planning and knowledge discovery in application areas such as bioinformatics, speech and image analysis. Most, however, are designed to deal with static processes which will not change over time. Some processes - such as speech, biological information and brain signals - are not static, however, and in these cases different models need to be used which can trace, and adapt to, the changes in the processes in an incremental, on-line mode, and often in real time. This book presents generic computational models and techniques that can be used for the development of evolving, adaptive modelling systems. The models and techniques used are connectionist-based (as the evolving brain is a highly suitable paradigm) and, where possible, existing connectionist models have been used and extended. The first part of the book covers methods and techniques, and the second focuses on applications in bioinformatics, brain study, speech, image, and multimodal systems. It also includes an extensive bibliography and an extended glossary. Evolving Connectionist Systems is aimed at anyone who is interested in developing adaptive models and systems to solve challenging real world problems in computing science or engineering. It will also be of interest to researchers and students in life sciences who are interested in finding out how information science and intelligent information processing methods can be applied to their domains.
IJCNN International Joint Conference on Neural Networks
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 812
Book Description
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 812
Book Description
Advances in Neural Networks - ISNN 2006
Author: Jun Wang
Publisher: Springer Science & Business Media
ISBN: 3540344829
Category : Computers
Languages : en
Pages : 1429
Book Description
This is Volume III of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.
Publisher: Springer Science & Business Media
ISBN: 3540344829
Category : Computers
Languages : en
Pages : 1429
Book Description
This is Volume III of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.
The Semantics of Relationships
Author: R. Green
Publisher: Springer Science & Business Media
ISBN: 9401700737
Category : Computers
Languages : en
Pages : 237
Book Description
The genesis of this volume was the participation of the editors in an ACMlSIGIR (Association for Computing Machinery/Special Interest Group on Information Retrieval) workshop entitled "Beyond Word Relations" (Hetzler, 1997). This workshop examined a number of relationship types with significance for information retrieval beyond the conventional topic-matching relationship. From this shared participation came the idea for an edited volume on relationships, with chapters to be solicited from researchers and practitioners throughout the world. Ultimately, one volume became two volumes. The first volume, Relationships in the Organization of Knowledge (Bean & Green, 200 I), examines the role of relationships in knowledge organization theory and practice, with emphasis given to thesaural relationships and integration across systems, languages, cultures, and disciplines. This second volume examines relationships in a broader array of contexts. The two volumes should be seen as companions, each informing the other. As with the companion volume, we are especially grateful to the authors who willingly accepted challenges of space and time to produce chapters that summarize extensive bodies of research. The value of the volume clearly resides in the quality of the individual chapters. In naming this volume The Semantics of Relationships: An Interdisciplinary Perspective, we wanted to highlight the fact that relationships are not just empty connectives. Relationships constitute important conceptual units and make significant contributions to meaning.
Publisher: Springer Science & Business Media
ISBN: 9401700737
Category : Computers
Languages : en
Pages : 237
Book Description
The genesis of this volume was the participation of the editors in an ACMlSIGIR (Association for Computing Machinery/Special Interest Group on Information Retrieval) workshop entitled "Beyond Word Relations" (Hetzler, 1997). This workshop examined a number of relationship types with significance for information retrieval beyond the conventional topic-matching relationship. From this shared participation came the idea for an edited volume on relationships, with chapters to be solicited from researchers and practitioners throughout the world. Ultimately, one volume became two volumes. The first volume, Relationships in the Organization of Knowledge (Bean & Green, 200 I), examines the role of relationships in knowledge organization theory and practice, with emphasis given to thesaural relationships and integration across systems, languages, cultures, and disciplines. This second volume examines relationships in a broader array of contexts. The two volumes should be seen as companions, each informing the other. As with the companion volume, we are especially grateful to the authors who willingly accepted challenges of space and time to produce chapters that summarize extensive bodies of research. The value of the volume clearly resides in the quality of the individual chapters. In naming this volume The Semantics of Relationships: An Interdisciplinary Perspective, we wanted to highlight the fact that relationships are not just empty connectives. Relationships constitute important conceptual units and make significant contributions to meaning.
Decision Technologies for Computational Finance
Author: Apostolos-Paul N. Refenes
Publisher: Springer Science & Business Media
ISBN: 1461556252
Category : Business & Economics
Languages : en
Pages : 472
Book Description
This volume contains selected papers that were presented at the International Conference COMPUTATIONAL FINANCE 1997 held at London Business School on December 15-17 1997. Formerly known as Neural Networks in the Capital Markets (NNCM), this series of meetings has emerged as a truly multi-disciplinary international conference and provided an international focus for innovative research on the application of a multiplicity of advanced decision technologies to many areas of financial engineering. It has drawn upon theoretical advances in financial economics and robust methodological developments in the statistical, econometric and computer sciences. To reflect its multi-disciplinary nature, the NNCM conference has adopted the new title COMPUTATIONAL FINANCE. The papers in this volume are organised in six parts. Market Dynamics and Risk, Trading and Arbitrage strategies, Volatility and Options, Term-Structure and Factor models, Corporate Distress Models and Advances on Methodology. This years' acceptance rate (38%) reflects both the increasing interest in the conference and the Programme Committee's efforts to improve the quality of the meeting year-on-year. I would like to thank the members of the programme committee for their efforts in refereeing the papers. I also would like to thank the members of the computational finance group at London Business School and particularly Neil Burgess, Peter Bolland, Yves Bentz, and Nevil Towers for organising the meeting.
Publisher: Springer Science & Business Media
ISBN: 1461556252
Category : Business & Economics
Languages : en
Pages : 472
Book Description
This volume contains selected papers that were presented at the International Conference COMPUTATIONAL FINANCE 1997 held at London Business School on December 15-17 1997. Formerly known as Neural Networks in the Capital Markets (NNCM), this series of meetings has emerged as a truly multi-disciplinary international conference and provided an international focus for innovative research on the application of a multiplicity of advanced decision technologies to many areas of financial engineering. It has drawn upon theoretical advances in financial economics and robust methodological developments in the statistical, econometric and computer sciences. To reflect its multi-disciplinary nature, the NNCM conference has adopted the new title COMPUTATIONAL FINANCE. The papers in this volume are organised in six parts. Market Dynamics and Risk, Trading and Arbitrage strategies, Volatility and Options, Term-Structure and Factor models, Corporate Distress Models and Advances on Methodology. This years' acceptance rate (38%) reflects both the increasing interest in the conference and the Programme Committee's efforts to improve the quality of the meeting year-on-year. I would like to thank the members of the programme committee for their efforts in refereeing the papers. I also would like to thank the members of the computational finance group at London Business School and particularly Neil Burgess, Peter Bolland, Yves Bentz, and Nevil Towers for organising the meeting.
Neural Nets WIRN Vietri-99
Author: Maria Marinaro
Publisher: Springer Science & Business Media
ISBN: 1447108779
Category : Computers
Languages : en
Pages : 429
Book Description
From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains a selection of papers from WIRN Vietri-99, the 11th Italian Workshop on Neural Nets. This annual event, sponsored, amongst others, by the IEEE Neural Networks Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of topics within neural networks, including pattern recognition, signal and image processing, mathematical models, neuro-fuzzy models and economics applications.
Publisher: Springer Science & Business Media
ISBN: 1447108779
Category : Computers
Languages : en
Pages : 429
Book Description
From its early beginnings in the fifties and sixties, the field of neural networks has been steadily developing to become one of the most interdisciplinary areas of research within computer science. This volume contains a selection of papers from WIRN Vietri-99, the 11th Italian Workshop on Neural Nets. This annual event, sponsored, amongst others, by the IEEE Neural Networks Council and the INNS/SIG Italy, brings together the best of research from all over the world. The papers cover a range of topics within neural networks, including pattern recognition, signal and image processing, mathematical models, neuro-fuzzy models and economics applications.
Data Engineering and Data Science
Author: Kukatlapalli Pradeep Kumar
Publisher: John Wiley & Sons
ISBN: 1119841879
Category : Mathematics
Languages : en
Pages : 469
Book Description
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.
Publisher: John Wiley & Sons
ISBN: 1119841879
Category : Mathematics
Languages : en
Pages : 469
Book Description
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.