Download or read book Using Fourier convergence analysis for effective learning in max min neural networks written by Kia Fock Loe and published by . This book was released on 1996 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real- valued domains. As such, neural networks that employ max-min activation functions have been a subject of interest in recent years. Since max-min functions are not strictly differentiable, many ad hoc learning methods for such max-min neural networks have been proposed in the literature. In this technical report, we propose a mathematically sound learning method based on using Fourier convergence analysis to derive a gradient descent technique for max-min error functions. This method is then applied to two models: a feedforward fuzzy-neural network and a recurrent max-min neural network. We show how a 'typical' fuzzy-neural network model employing max- min activation functions can be trained to perform function approximation; its performance was found to be better than that of a conventional feedforward neural network. We also propose a novel recurrent max-min neural network model which is trained to perform grammatical inference as an application example. Comparisons are made between this model and recurrent neural networks that use conventional sigmoidal activation fuctions; such recurrent sigmoidal networks are known to be difficult to train and generalize poorly on long strings. The comparisons show that our model not only performs better in terms of learning speed and generalization, its final weight configuration allows a DFQ to be extracted in a straighforward manner. However, it has a potential drawback: the minimal network size required for successful convergence grows with increasing language depth and complexity. Nevertheless, we are able to demonstrate that our proposed gradient descent technique does allow max-min neural networks to learn effectively. Our leaning method should be extensible to other neural networks that have non-differentiable activation functions."
Download or read book IJCAI 97 written by International Joint Conferences on Artificial Intelligence and published by Morgan Kaufmann. This book was released on 1997 with total page 1720 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the International Joint Conference on Artificial Intelligence written by and published by . This book was released on 1997 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Effective Learning in Max min Neural Networks written by Loo Nin Teow and published by . This book was released on 1997 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Neural Nets and Genetic Algorithms written by David W. Pearson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are subjects of the contributions to this volume. There are contributions reporting successful applications of the technology to the solution of industrial/commercial problems. This may well reflect the maturity of the technology, notably in the sense that 'real' users of modelling/prediction techniques are prepared to accept neural networks as a valid paradigm. Theoretical issues also receive attention, notably in connection with the radial basis function neural network. Contributions in the field of genetic algorithms reflect the wide range of current applications, including, for example, portfolio selection, filter design, frequency assignment, tuning of nonlinear PID controllers. These techniques are also used extensively for combinatorial optimisation problems.
Download or read book Chemometric Methods in Analytical Spectroscopy Technology written by Xiaoli Chu and published by Springer Nature. This book was released on 2022-05-23 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.
Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Download or read book Wavelets In Soft Computing written by Marc Thuillard and published by World Scientific. This book was released on 2001-06-15 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of integration of wavelet theory and multiresolution analysis into soft computing. It is the first book on hybrid methods combining wavelet analysis with fuzzy logic, neural networks or genetic algorithms. Much attention is given to new approaches (fuzzy-wavelet) that permit one to develop, using wavelet techniques, linguistically interpretable fuzzy systems from data. The book also introduces the reader to wavelet-based genetic algorithms and multiresolution search. A special place is given to methods that have been implemented in real world applications, particularly the different techniques combining fuzzy logic or neural networks with wavelet theory.
Download or read book A Wavelet Tour of Signal Processing written by Stephane Mallat and published by Elsevier. This book was released on 1999-09-14 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and ÉcolePolytechnique in Paris. - Provides a broad perspective on the principles and applications of transient signal processing with wavelets - Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms - Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements - Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet - Content is accessible on several level of complexity, depending on the individual reader's needs New to the Second Edition - Optical flow calculation and video compression algorithms - Image models with bounded variation functions - Bayes and Minimax theories for signal estimation - 200 pages rewritten and most illustrations redrawn - More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics
Download or read book Applied Artificial Intelligence written by Swati V. Shinde and published by CRC Press. This book was released on 2023-09-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.
Download or read book Visual Communications and Image Processing 92 written by and published by . This book was released on 1992 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Visual Communications and Image Processing written by and published by . This book was released on 1992 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Index Medicus written by and published by . This book was released on 2004 with total page 2520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.
Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.
Download or read book Cyber Security Cryptography and Machine Learning written by Shlomi Dolev and published by Springer. This book was released on 2019-06-17 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019, held in Beer-Sheva, Israel, in June 2019. The 18 full and 10 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Download or read book Artificial Neural Nets and Genetic Algorithms written by and published by . This book was released on 1995 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Arithmetic Complexity of Computations written by Shmuel Winograd and published by SIAM. This book was released on 1980-01-01 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on finding the minimum number of arithmetic operations needed to perform the computation and on finding a better algorithm when improvement is possible. The author concentrates on that class of problems concerned with computing a system of bilinear forms. Results that lead to applications in the area of signal processing are emphasized, since (1) even a modest reduction in the execution time of signal processing problems could have practical significance; (2) results in this area are relatively new and are scattered in journal articles; and (3) this emphasis indicates the flavor of complexity of computation.
