Haibo He

Wen Yu

The three volume set LNCS 5551/5552/5553 constitutes the refereed proceedings of the 6th International Symposium on Neural Networks, ISNN 2009, held in Wuhan, China in May 2009. The 409 revised papers presented were carefully reviewed and selected from a total of 1.235 submissions. The papers are organized in 20 topical sections on theoretical analysis, stability, time-delay neural networks, machine learning, neural modeling, decision making systems, fuzzy systems and fuzzy neural networks, support vector machines and kernel methods, genetic algorithms, clustering and classification, pattern recognition, intelligent control, optimization, robotics, image processing, signal processing, biomedical applications, fault diagnosis, telecommunication, sensor network and transportation systems, as well as applications.

6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings

Advances in Neural Networks - ISNN 2009

Cesare Alippi

Marios Polycarpou

Derong Liu

Huaguang Zhang

The three-volume set LNCS 6675, 6676 and 6677 constitutes the refereed proceedings of the 8th International Symposium on Neural Networks, ISNN 2011, held in Guilin, China, in May/June 2011. The total of 215 papers presented in all three volumes were carefully reviewed and selected from 651 submissions. The contributions are structured in topical sections on computational neuroscience and cognitive science; neurodynamics and complex systems; stability and convergence analysis; neural network models; supervised learning and unsupervised learning; kernel methods and support vector machines; mixture models and clustering; visual perception and pattern recognition; motion, tracking and object recognition; natural scene analysis and speech recognition; neuromorphic hardware, fuzzy neural networks and robotics; multi-agent systems and adaptive dynamic programming; reinforcement learning and decision making; action and motor control; adaptive and hybrid intelligent systems; neuroinformatics and bioinformatics; information retrieval; data mining and knowledge discovery; and natural language processing.

8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Proceedings

Advances in Neural Networks -- ISNN 2011

8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Prodceedings, Part III

Nian Zhang

This book and its companion volumes, LNCS vols. 5551, 5552 and 5553, constitute the proceedings of the 6th International Symposium on Neural Networks (ISNN 2009), held during May 26–29, 2009 in Wuhan, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural n- works and related fields, with a successful sequence of ISNN symposia held in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), and Beijing (2008). Following the tradition of the ISNN series, ISNN 2009 provided a high-level inter- tional forum for scientists, engineers, and educators to present state-of-the-art research in neural networks and related fields, and also to discuss with international colleagues on the major opportunities and challenges for future neural network research. Over the past decades, the neural network community has witnessed tremendous - forts and developments in all aspects of neural network research, including theoretical foundations, architectures and network organizations, modeling and simulation, - pirical study, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, have provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large-scale, and n- worked brain-like intelligent systems. This long-term goal can only be achieved with the continuous efforts of the community to seriously investigate different issues of the neural networks and related fields.

6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part I

Yunqian Ma

The first book of its kind to review the current status andfuture direction of the exciting new branch of machinelearning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system canlearn when it is provided with imbalanced data. Solving imbalancedlearning problems is critical in numerous data-intensive networkedsystems, including surveillance, security, Internet, finance,biomedical, defense, and more. Due to the inherent complexcharacteristics of imbalanced data sets, learning from such datarequires new understandings, principles, algorithms, and tools totransform vast amounts of raw data efficiently into information andknowledge representation. The first comprehensive look at this new branch of machinelearning, this book offers a critical review of the problem ofimbalanced learning, covering the state of the art in techniques,principles, and real-world applications. Featuring contributionsfrom experts in both academia and industry, Imbalanced Learning:Foundations, Algorithms, and Applications provides chaptercoverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support VectorMachines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced ClassDistribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, andApplications will help scientists and engineers learn how totackle the problem of learning from imbalanced datasets, and gaininsight into current developments in the field as well as futureresearch directions.

Foundations, Algorithms, and Applications

Imbalanced Learning

6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part II

8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Proceedings, Part II

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.

Self-Adaptive Systems for Machine Intelligence

6th International Symposium on Neural Networks, Isnn 2009 Wuhan, China, May 26-29, 2009 Proceedings

Advances in Neural Networks Isnn 2009

8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29--June 1, 2011, Prodceedings

Haibo He

Books

Your next favorite book is out there