What Is Radial Basis Networks
A radial basis function network is a type of artificial neural network that is used in the field of mathematical modeling. This type of network employs radial basis functions as its activation functions. The output of the network is a linear combination of the neuron parameters and the radial basis functions of the inputs to the network. Radial basis function networks have a wide range of applications, some of which include the approximation of functions, the prediction of time series, the classification of data, and the control of systems. In their study from 1988, Broomhead and Lowe, who were both researchers at the Royal Signals and Radar Establishment, were the ones who initially formulated the ideas.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Radial basis function network
Chapter 2: Gradient
Chapter 3: Radial basis function
Chapter 4: Radial basis function kernel
Chapter 5: Functional derivative
Chapter 6: Jacobian matrix and determinant
Chapter 7: Laplace's equation
Chapter 8: Laplace operator
Chapter 9: Multiple integral
Chapter 10: Polyharmonic spline
(II) Answering the public top questions about radial basis networks.
(III) Real world examples for the usage of radial basis networks in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of radial basis networks.
What Is Artificial Intelligence Series
The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
A radial basis function network is a type of artificial neural network that is used in the field of mathematical modeling. This type of network employs radial basis functions as its activation functions. The output of the network is a linear combination of the neuron parameters and the radial basis functions of the inputs to the network. Radial basis function networks have a wide range of applications, some of which include the approximation of functions, the prediction of time series, the classification of data, and the control of systems. In their study from 1988, Broomhead and Lowe, who were both researchers at the Royal Signals and Radar Establishment, were the ones who initially formulated the ideas.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Radial basis function network
Chapter 2: Gradient
Chapter 3: Radial basis function
Chapter 4: Radial basis function kernel
Chapter 5: Functional derivative
Chapter 6: Jacobian matrix and determinant
Chapter 7: Laplace's equation
Chapter 8: Laplace operator
Chapter 9: Multiple integral
Chapter 10: Polyharmonic spline
(II) Answering the public top questions about radial basis networks.
(III) Real world examples for the usage of radial basis networks in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of radial basis networks.
What Is Artificial Intelligence Series
The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.